Testing the constancy of Spearman’s rho in multivariate time series

@article{Kojadinovic2014TestingTC,
  title={Testing the constancy of Spearman’s rho in multivariate time series},
  author={Ivan Kojadinovic and Jean‐François Quessy and Tom Rohmer},
  journal={Annals of the Institute of Statistical Mathematics},
  year={2014},
  volume={68},
  pages={929-954}
}
A class of tests for change-point detection designed to be particularly sensitive to changes in the cross-sectional rank correlation of multivariate time series is proposed. The derived procedures are based on several multivariate extensions of Spearman’s rho. Two approaches to carry out the tests are studied: the first one is based on resampling and the second one consists of estimating the asymptotic null distribution. The asymptotic validity of both techniques is proved under the null for… 

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Title Some Nonparametric Tests for Change-point Detection in Possibly Multivariate Observations

July 24, 2015 Type Package Title Some Nonparametric Tests for Change-Point Detection in Possibly Multivariate Observations Version 0.1-6 Date 2015-07-23 Author Ivan Kojadinovic Maintainer Ivan

References

SHOWING 1-10 OF 44 REFERENCES

Detecting changes in cross-sectional dependence in multivariate time series

Multivariate Kendall's tau for change‐point detection in copulas

Statistical procedures for the detection of a change in the dependence structure of a series of multivariate observations are studied in this work. The test statistics that are proposed are $L_1$,

A fluctuation test for constant Spearman's rho with nuisance-free limit distribution

Theoretical efficiency comparisons of independence tests based on multivariate versions of Spearman’s rho

Schmid and Schmidt (Stat Probab Lett 77:407–416, 2007) recently described multivariate extensions to the population and sample versions of Spearman’s rank correlation coefficient. In this paper, the

Testing for Change Points in Time Series

This article considers the CUSUM-based (cumulative sum) test for a change point in a time series. In the case of testing for a mean shift, the traditional Kolmogorov–Smirnov test statistic involves a

A fluctuation test for constant Spearman’s rho

We propose a CUSUM type test for constant correlation that goes beyond a previously suggested correlation constancy test by considering Spearman’s rho in arbitrary dimensions. By using copula-based

Automatic Block-Length Selection for the Dependent Bootstrap

TLDR
This work proposes practically useful estimators of the optimal block size for the aforementioned block bootstrap methods and proposes a new notion of finite-sample “attainable” relative efficiency based on the notion of spectral estimation via the flat-top lag-windows of Politis and Romano.

Multivariate Extensions of Spearman's Rho and Related Statistics

A non-parametric test of independence ∗

We propose a new class of nonparametric tests for the supposition of independence between two continuous random variables X and Y. Given a sample of (X,Y ), the tests are based on the size of the