Non-Parametric Change Point Problems Using Multipliers

18 Pages Posted: 22 Apr 2012  

Bruno Remillard

Department of Decision Sciences, HEC Montreal

Date Written: April 21, 2012

Abstract

Trying to perform non-parametric change point tests for multivariate data using empirical processes is much more difficult that in the univariate case, since the limiting distribution depends on the unknown joint distribution function or its associated copula. In order to solve this problem, we extend the multiplier central limit theorem to empirical processes of pseudo-observations to build asymptotically independent copies of these processes. Examples of applications to change point problems for i.i.d observations and innovations of dynamic models are given, both for the full distribution and the associated copula.

Keywords: Multipliers, change point, bootstrap, p-value, empirical process, pseudo-observations, time series, copula

JEL Classification: C14, C12, C22, C52

Suggested Citation

Remillard, Bruno, Non-Parametric Change Point Problems Using Multipliers (April 21, 2012). Available at SSRN: https://ssrn.com/abstract=2043632 or http://dx.doi.org/10.2139/ssrn.2043632

Bruno Remillard (Contact Author)

Department of Decision Sciences, HEC Montreal ( email )

3000 Côte-Sainte-Catherine Road
Montreal, QC H2S1L4
Canada
514-340-6794 (Phone)

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