multiCUMSUM {starvars} | R Documentation |
Multivariate CUMSUM test
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 |
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 |
Omega Test statistics |
a matrix of test statistics on the presence of a number of co-break equal to |
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)