Climate changepoint (homogenization) methods abound today, with a myriad of techniques
existing in both the climate and statistics literature. Unfortunately, the appropriate …

A MOSUM procedure for the estimation of multiple random change points Page 1 Bernoulli
24(1), 2018, 526–564 DOI: 10.3150/16-BEJ887 A MOSUM procedure for the estimation of …

Change point detection in sequences of functional data is examined where the functional
observations are dependent. Of particular interest is the case where the change point is an …

Evaluating stationarity via change-point alternatives with applications to fMRI data Page 1 The
Annals of Applied Statistics 2012, Vol. 6, No. 4, 1906–1948 DOI: 10.1214/12-AOAS565 © …

This paper addresses the problem of localizing and inferring multiple change points, in non-
parametric multivariate time series settings. Specifically, we consider a multivariate time …

We study the problem of change-point detection and localisation for functional data
sequentially observed on a general $ d $-dimensional space, where we allow the functional …

The segmentation of a time series into piecewise stationary segments is an important
problem both in time series analysis and signal processing. In the presence of multiscale …

TFT-bootstrap: Resampling time series in the frequency domain to obtain replicates in the
time domain Page 1 The Annals of Statistics 2011, Vol. 39, No. 3, 1427–1470 DOI: 10.1214/10-AOS868 …

We propose a methodology for detecting multiple change points in the mean of an otherwise
stationary, autocorrelated, linear time series. It combines solution path generation based on …

In this paper, we study change-point testing for high-dimensional linear models, an
important problem that has not been well explored in the literature. Specifically, we propose …