drbats.simul | R Documentation |
Main simulation function
drbats.simul( N = 10, P = 150, t.range = c(0, 1000), b.range = c(0.2, 0.4), c.range = c(0.6, 0.8), b.sd = 2, c.sd = 2, a.range = c(-0.4, 0.4), y.range = c(0, 10), amp = 10, per = 12, data.type = "sparse", breaks = 15, sigma2 = 0.2, seed = NULL )
N |
integer number of functions to simulate (default = 10) |
P |
a number of observation times (default = 150) |
t.range |
a range of times in which to place the P observations (default = c(1, 1000)) |
b.range |
a vector giving the range of values for the mean of the first mode (default b.range = c(0.2, 0.4)) |
c.range |
a vector giving the range of values for the mean of the second mode (default c.range = c(0.6, 0.8)) |
b.sd |
the standard deviation for the first mode (default b.sd = 2) |
c.sd |
the standard deviation for the second mode (default c.sd = 2) |
a.range |
a vector giving the range of values for the slope (default a.range = c(-0.4, 0.4)) |
y.range |
a vector giving the range of values for the intercept (default y.range = c(0, 10)) |
amp |
the amplitude of the cosine function (default = 10) |
per |
the periodicity of the cosine function (default = 12) |
data.type |
string indicating type of functions (options :sparse, sparse.tend, sparse.tend.cos) |
breaks |
number of breaks in the histogram basis |
sigma2 |
the precision of the error terms (default = 0.2) |
seed |
integer specification of a seed (default = NULL) |
Y.simul a list containing a matrix Y, a matrix beta, and a matrix epsilon
t.simul a matrix of simulated observation times
X the underlying signal to build the data, see DataSimulationandProjection vignette
proj.pca the outputs of the function pca.proj.Xt
wlu the outputs of the function W.QR
Gabrielle Weinrott
res <- drbats.simul(N = 5, P = 100, t.range = c(5, 100), breaks = 8) X <- res$X t <- res$t.simul # To plot the observations, ie the rows matplot(t(t), t(X), type = 'l', xlab = "Time", ylab = "X")
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