testVAR {LSVAR} | R Documentation |
Function to generate a VAR process
Description
A function to generate synthetic time series process based on the given structure
Usage
testVAR(
n,
p,
struct = c("sparse", "low rank", "LS")[1],
sp_density = 0.1,
signal = NULL,
rank = NULL,
singular_vals,
spectral_radius = 0.9,
sigma = NULL,
skip = 50,
seed = 1
)
Arguments
n |
the length of time series |
p |
the number of multivariate time series |
struct |
a character string indicating the structure of the transition matrix, here are three options: sparse, low rank and LS (low rank plus sparse) |
sp_density |
a numeric value, indicating the sparsity density of sparse components, default is 0.1 |
signal |
a numeric value, indicating the magnitude of transition matrix |
rank |
a positive integer, the rank for low rank component |
singular_vals |
a numeric vector, indicating the singular values for the low rank component, the length of singular value must equal to the rank |
spectral_radius |
a numeric value, controlling the stability of the process, default is 0.9 |
sigma |
a numeric matrix, indicating the covariance matrix of noise term |
skip |
a numeric value, indicating the number of skipped time points in the beginning of the process |
seed |
an integer, indicating the seed for random seed. |
Value
A list object, including
- series
the generated time series
- noise
the noise term
- model_param
true transition matrix
Examples
n <- 300; p <- 15
signal <- 0.75
rank <- 3
singular_vals <- c(1, 0.75, 0.5)
try <- testVAR(n, p, struct = "LS", signal = signal, rank = rank,
singular_vals = singular_vals)
data <- as.matrix(try$series)