summary.SNSeg_Uni: Summary of SN-based change-point estimates for univariate or...

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

Summary of SN-based change-point estimates for univariate or bivariate time series (testing the change in correlation between bivariate time series)

Description

Summary method for objects of class SNSeg_Uni

Usage

## S3 method for class 'SNSeg_Uni'
summary(object, ...)

Arguments

object	a SNSeg_Uni object
...	not in use

Details

Provide information about estimated change-point locations, the parameter tested by SN-based procedures, the confidence level, the grid_size, and the critical value of the SN-based test.

Examples

set.seed(7)
ts <- MAR_Variance(2, "V1")
ts <- ts[,2]
# test the change in a single parameter (variance)
# grid_size defined
result <- SNSeg_Uni(ts, paras_to_test = "variance", confidence = 0.9,
                    grid_size_scale = 0.05, grid_size = 67,
                    plot_SN = FALSE, est_cp_loc = TRUE)
summary(result)

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