ftsspec: Spectral Density Estimation and Comparison for Functional Time Series

sim.name="locfreq--wiener-T64-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3000 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T64-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3001 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T64-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3002 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T64-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3015 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T64-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3016 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T64-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3017 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T64-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3030 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T64-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3031 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T64-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3032 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T64-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3045 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T64-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3046 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T64-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3047 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T64-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3060 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T64-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3061 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T64-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3062 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T64-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3075 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T64-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3076 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T64-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=64 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3077 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T128-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3003 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T128-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3004 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T128-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3005 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T128-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3018 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T128-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3019 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T128-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3020 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T128-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3033 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T128-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3034 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T128-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3035 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T128-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3048 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T128-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3049 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T128-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3050 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T128-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3063 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T128-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3064 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T128-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3065 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T128-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3078 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T128-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3079 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T128-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=128 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3080 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T256-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3006 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T256-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3007 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T256-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3008 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T256-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3021 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T256-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3022 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T256-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3023 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T256-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3036 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T256-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3037 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T256-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3038 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T256-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3051 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T256-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3052 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T256-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3053 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T256-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3066 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T256-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3067 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T256-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3068 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T256-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3081 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T256-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3082 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T256-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=256 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3083 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T512-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3009 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T512-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3010 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T512-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3011 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T512-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3024 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T512-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3025 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T512-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3026 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T512-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3039 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T512-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3040 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T512-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3041 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T512-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3054 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T512-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3055 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T512-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3056 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T512-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3069 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T512-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3070 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T512-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3071 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T512-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3084 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T512-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3085 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T512-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=512 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3086 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T1024-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3012 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T1024-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3013 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T1024-ma.diff0-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3014 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T1024-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3027 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T1024-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3028 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T1024-ma.diff0.1-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.1 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3029 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T1024-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3042 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T1024-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3043 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T1024-ma.diff0.2-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.2 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3044 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T1024-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3057 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T1024-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3058 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T1024-ma.diff0.3-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.3 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3059 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T1024-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3072 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T1024-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3073 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T1024-ma.diff0.4-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.4 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3074 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--wiener-T1024-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="wiener" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3087 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--white-noise-T1024-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="white-noise" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3088 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################


sim.name="locfreq--student5-T1024-ma.diff0.5-a.smooth0-d.n20" # The name of the simulation
B=1000 # The number of replicates
d.ts=20 # Dimension of the FTS
d.n=20 # Dimension of the noise process driving the MA
noise.type="student5" # 
ma.scale=c(-1.4,2.3,-2) # scaling of the MA filter
ma.diff.index=3 # which index of the MA filter differs between the two FTS
ma.diff=0.5 # by how much it differs
a.smooth.coef=0 # coefficient for scaling the entries of the MA filter dimensionwise (not varying in these simulations)
T.len=1024 # Length of the FTS that is simulated
K=5 # Number of subspaces into which the test is projected
simulation.seed=3089 # simulation seed (for reproducibility)
subgrid.density=10 # density of the (frequency) subgrid on which the two spectral density operators are compared
subgrid.density.relative.to.bandwidth=TRUE # is subgrid.density given relatively to the bandwidth?



##################################################
stavakol/ftsspec documentation built on May 30, 2019, 10:43 a.m.
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stavakol/ftsspec
Spectral Density Estimation and Comparison for Functional Time Series

simulations-code/localize-freq-SIMparameters.R
In stavakol/ftsspec: Spectral Density Estimation and Comparison for Functional Time Series

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stavakol/ftsspec Spectral Density Estimation and Comparison for Functional Time Series

simulations-code/localize-freq-SIMparameters.R In stavakol/ftsspec: Spectral Density Estimation and Comparison for Functional Time Series

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stavakol/ftsspec
Spectral Density Estimation and Comparison for Functional Time Series

simulations-code/localize-freq-SIMparameters.R
In stavakol/ftsspec: Spectral Density Estimation and Comparison for Functional Time Series
