mvn.sim.2.cps

A positive integer, which defines the length of the time series.
It must be a multiple of 3 since change points occur at time points T/3
and 2T/3.

nobs

A positive integer number indicating the dimensionality of the
time series. <code>n_ser</code> must be equal to or larger than 8 as <code>mvn.sim.2.cps</code>
generates 3 different network structures among 8 connected nodes. The remaining
variables are generated as independent data.

n_ser

A positive integer with default value equal to 101.
It is used to ensure reproducibility.

seed

This function simulates a multivariate normal data set with 2
change points in the network structure.

Implements the Vine Copula Change Point (VCCP) methodology for the estimation of the number and location of multiple change points in the vine copula structure of multivariate time series. The method uses vine copulas, various state-of-the-art segmentation methods to identify multiple change points, and a likelihood ratio test or the stationary bootstrap for inference. The vine copulas allow for various forms of dependence between time series including tail, symmetric and asymmetric dependence. The functions have been extensively tested on simulated multivariate time series data and fMRI data. For details on the VCCP methodology, please see Xiong & Cribben (2021).

mvn.sim.2.cps: Simulate multivariate normal data with 2 change points

Description

Usage

Arguments

Value

Examples