sim_hdchange_no_nbd {L2hdchange} | R Documentation |
Simulate data without neighbourhood
Description
Simulate data without neighbourhood
Usage
sim_hdchange_no_nbd(
n = 200,
p = 30,
S = 30,
tau = c(40, 100, 160),
dist_info = list(dist = "normal", dependence = "iid", param = 1),
jump_max = c(2, 2, 1.5)
)
Arguments
n |
Number of time series observations. |
p |
Number of individuals. |
S |
Number of individuals with jumps. |
tau |
An array of length |
dist_info |
A list specifying the distribution of the innovation. |
jump_max |
An array of length |
Details
'dist_info' should be a list containing the following items:
dist: distribution of the innovations, either "normal" or "t".
dependence: iid or MA(
\infty
), either "iid" or "MA_inf".param = parameter of the distribution, standard deviation for normal distribution and degree of freedom for t distribution
See ts_hdchange()
for example.
Value
A p \times n
simulated data matrix.
Examples
data_no_nbd <- sim_hdchange_no_nbd(n = 200,
p = 30,
S = 30,
tau = c(40, 100, 160),
dist_info =
list(dist = "normal", dependence = "MA_inf", param = 1),
jump_max = c(2, 2, 1.5))
[Package L2hdchange version 1.0 Index]