plot.SNSeg_Multi: Plotting the output for multivariate time series with...

In SNSeg: Self-Normalization(SN) Based Change-Point Estimation for Time Series

Plotting the output for multivariate time series with dimension no greater than 10

Description

Plotting method for S3 objects of class SNSeg_Multi

Usage

## S3 method for class 'SNSeg_Multi'
plot(x, cpts.col = "red", ...)

Arguments

x	a SNSeg_Multi object
cpts.col	a specification for the color of the vertical lines at the change point estimators, see par
...	additional graphical arguments, see plot and abline

Details

The location of each change point estimator is plotted as a vertical line against the input time series.

Examples

# Please run this function before simulation
exchange_cor_matrix <- function(d, rho){
  tmp <- matrix(rho, d, d)
  diag(tmp) <- 1
  return(tmp)
}

# simulation of multivariate time series
library(mvtnorm)
set.seed(10)
d <- 5
n <- 600
nocp <- 5
cp_sets <- round(seq(0, nocp+1 ,1)/(nocp+1)*n)
mean_shift <- rep(c(0,2),100)[1:(length(cp_sets)-1)]/sqrt(d)
rho_sets <- 0.2
sigma_cross <- list(exchange_cor_matrix(d,0))
ts <- MAR_MTS_Covariance(n, 2, rho_sets, cp_sets = c(0,n), sigma_cross)
ts <- ts[1][[1]]

# Test for the change in multivariate means
# grid_size defined
result <- SNSeg_Multi(ts, paras_to_test = "mean", confidence = 0.99,
                      grid_size_scale = 0.05, grid_size = 45)
# plot method
plot(result)

SNSeg documentation built on June 22, 2024, 10:50 a.m.