multiCUMSUM: Multivariate CUMSUM test

In starvars: Vector Logistic Smooth Transition Models Estimation and Prediction

Description

Function returns the test statistics for the presence of co-breaks in a set of multivariate time series.

Usage

multiCUMSUM(data, conf.level = 0.95, max.breaks = 7)

Arguments

data	a (T x N) matrix or data.frame containing the N time series over period T
conf.level	Confidence level. By default set to 0.95
max.breaks	Integer, determines the highest number of common breaks from 1 to 7.

Value

Lambda Test statistics	a matrix of test statistics on the presence of a number of co-break equal to max.breaks in the conditional mean
Omega Test statistics	a matrix of test statistics on the presence of a number of co-break equal to max.breaks in the conditional variance
Break location	the index and the Date where the common breaks are located

Author(s)

Andrea Bucci and Giulio Palomba

References

Aue A., Hormann S., Horvath L.and Reimherr M. (2009), Break detection in the covariance structure of multivariate time series models. The Annals of Statistics. 37: 4046-4087 Bai J., Lumsdaine R. L. and Stock J. H. (1998), Testing For and Dating Common Breaks in Multivariate Time Series. Review of Economic Studies. 65: 395-432 Barassi M., Horvath L. and Yuqian Z. (2018), Change-Point Detection in the Conditional Correlation Structure of Multivariate Volatility Models. Journal of Business \& Economic Statistics

Examples

data(Realized)
testCS <- multiCUMSUM(Realized[,1:10], conf.level = 0.95)
print(testCS)

starvars documentation built on Jan. 18, 2022, 1:08 a.m.