Description Usage Arguments Details Value References Examples
Sample Irregular Functional Data
1 2 3 4 5 6 7 8 9 10 | irreg.fd(
mu = 0,
X = wiener.process(),
n = 100,
m = 5,
sig = NULL,
snr = 5,
domain = c(0, 1),
delta = 1
)
|
mu |
function, scalar or a vector defining the mean function; default value: |
X |
centered stochastic process defined by a function of the form
|
n |
sample size; default value: |
m |
a vector of sampling rate or scalar of average sampling rate or a function of the form |
sig |
standard deviation of measurement errors; if |
snr |
signal to noise ratio to determine |
domain |
the domain; default value: |
delta |
the proportion of the domain to be observed for each trajectory; default value: |
The number of observation for each trajectory is randomly generated by rpois(m)+1
. For each trajectory, the reference time Oi
is uniformly sampled from the interval [domain[1]+delta*L/2,domain[2]-delta*L/2]
, where L
is the length of domain
, and the design points for the trajectory is uniformly sampled from the interval [Oi-delta*L/2,Oi+delta*L/2]
.
a list with the following members
t
list of design points sorted in increasing order for each trajectory.
y
list of vectors of observations for each trajectory.
and with attributes sig
, snr
, domain
, delta
and
n*m
matrix of observations without measurement errors.
Lin2020synfd
1 2 3 4 5 6 7 8 | # Gaussian trajectories with constant mean function 1
Y <- irreg.fd(mu=1, X=gaussian.process(), n=10, m=5)
# trajectories froma a process defined via K-L representation
Y <- irreg.fd(mu=cos, X=kl.process(eigen.functions='FOURIER',distribution='LAPLACE'),n=10, m=5)
# trajectories with specified individual sampling rate
Y <- irreg.fd(mu=1, X=gaussian.process(cov=matern), n=10, m=rpois(10,3)+2)
|
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