wishartDataGeneration: Data Generation - Wishart

In grundy95/changepoint.cov: Implementation of Covariance Changepoint Methods

Description

Allows for easy generation of data containing covariance changepoints as described in \insertCiteRyan2020;textualchangepoint.cov

Usage

wishartDataGeneration(
  n,
  p,
  tau = c(1, n),
  Sigma = list(NA),
  shape = 5,
  scale = 1/5
)

Arguments

n	Number of time points.
p	Dimension of the time series.
tau	Vector of changepoint locations.
Sigma	List of segment covariances. Defaults to automatic generation.
shape	Shape parameter for generation of eigenvalues in transition matrix. Only used with automatic generation of segment covariances.
scale	Scale parameter for generation of eigenvalues in transition matrix. Only used with automatic generation of segment covariances.

Details

This function generates data that contain changes in covariance. If the covariance for each segment, Sigma, is given then data is generated from a $N(0,Sigma)$ for each segment. If the segment covariance aren't given then they are generated via simulating from Wishart distribution.

Value

List with elements:

• data Matrix of generated data with dimension n by p.

• cpts Location of the changepoints.

• Sigma List of covariance matrices of each segment.

References

\insertRef

Ryan2020changepoint.cov

See Also

cptCov, subspaceDataGeneration

Examples

set.seed(1)
dataObject <- wishartDataGeneration(n=100,p=4,tau=40)
dim(dataObject$data)
dataObject$cpts
dataObject$Sigma

grundy95/changepoint.cov documentation built on April 5, 2021, 6:21 p.m.