Sequential block bootstrap in a Hilbert space with application to change point analysis
Statistics Theory
2015-09-16 v2 Statistics Theory
Abstract
A new test for structural changes in functional data is investigated. It is based on Hilbert space theory and critical values are deduced from bootstrap iterations. Thus a new functional central limit theorem for the block bootstrap in a Hilbert space is required. The test can also be used to detect changes in the marginal distribution of random vectors, which is supplemented by a simulation study. Our methods are applied to hydrological data from Germany.
Cite
@article{arxiv.1412.0446,
title = {Sequential block bootstrap in a Hilbert space with application to change point analysis},
author = {Olimjon Sharipov and Johannes Tewes and Martin Wendler},
journal= {arXiv preprint arXiv:1412.0446},
year = {2015}
}