In this article, we develop a command, xthenreg, that implements the first-differenced
generalized method of moments estimation of the dynamic panel threshold model that Seo …

In large-scale panel data models with latent factors the number of factors and their loadings
may change over time. Treating the break date as unknown, this article proposes an …

Change point analysis aims to detect structural changes in a data sequence. It has always
been an active research area since it was introduced in the 1950s. In modern statistical …

Change-point inference in high-dimensional regression models under temporal dependence
Page 1 The Annals of Statistics 2024, Vol. 52, No. 3, 999–1026 https://doi.org/10.1214/24-AOS2380 …

Current diagnostic systems for Alzheimer's disease (AD) rely upon clinical signs and
symptoms, despite the fact that the multiplicity of clinical symptoms renders various …

This paper addresses the problem of localizing change points in high-dimensional linear
regression models with piecewise constant regression coefficients. We develop a dynamic …

This paper develops a new model and estimation procedure for panel data that allows us to
identify heterogeneous structural breaks. We model individual heterogeneity using a …

Detecting when the underlying distribution changes for the observed time series is a
fundamental problem arising in a broad spectrum of applications. In this paper, we study …

Background The combination of immune checkpoint inhibitors (ICIs) and anti-angiogenic
agents has shown promising efficacy in unresectable hepatocellular carcinoma (HCC), but …

For multiple change-points detection of high-dimensional time series, we provide asymptotic
theory concerning the consistency and the asymptotic distribution of the breakpoint statistics …