Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1149211 | Journal of Statistical Planning and Inference | 2017 | 15 Pages |
Abstract
We consider a multiple change-point problem: a finite sequence of independent random variables consists of segments given by a known number of the so-called change-points such that the underlying distribution differs from segment to segment. The task is to estimate these change-points under no further assumptions on the within-segment distributions. In this completely nonparametric framework the proposed estimator is defined as the maximizing point of weighted multivariate U-statistic processes. Under mild moment conditions we prove almost sure convergence and the rate of convergence.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Maik Döring,