get_cov_x_MAinf: The covariance matrix for generating random Gaussian vector

In L2hdchange: L2 Inference for Change Points in High-Dimensional Time Series

The covariance matrix for generating random Gaussian vector

Description

The covariance matrix for generating random Gaussian vector

Usage

get_cov_x_MAinf(n, b)

Arguments

n	Number of time series observations.
b	Bandwith parameter b = window\_size/n.

Value

The covariance matrix. See section 2.2 of Li et al. (2023).

References

Li, J., Chen, L., Wang, W. and Wu, W.B., 2022. \ell^2 Inference for Change Points in High-Dimensional Time Series via a Two-Way MOSUM. arXiv preprint arXiv:2208.13074.

Examples

# generate data
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))

# construct no_nbd object
ts_no_nbd <- ts_hdchange(data_no_nbd,
window_size = 30,
m = 8,
h = 1,
N_rep = 999,
alpha = 1e-5,
quantiles = c(0.01, 0.05, 0.1))

Cov_x_MAinf <- get_cov_x_MAinf(ts_no_nbd$n, ts_no_nbd$b)

L2hdchange documentation built on July 26, 2023, 6:06 p.m.