Change, dependence, and discovery: Celebrating the work of T.L. Lai

TL;DR

This paper reviews Tze Leung Lai's influential contributions to sequential analysis, highlighting his foundational work in hypothesis testing, changepoint detection, and applications in biostatistics.

Contribution

It provides a comprehensive overview of Lai's seminal theoretical and practical advancements in sequential analysis and changepoint detection.

Findings

Established fundamental optimality results for sequential probability ratio tests

Introduced new optimality criteria and efficient procedures for changepoint detection

Applied sequential analysis tools to biostatistics problems

Abstract

Tze Leung Lai made seminal contributions to sequential analysis, particularly in sequential hypothesis testing, changepoint detection and nonlinear renewal theory. His work established fundamental optimality results for the sequential probability ratio test and its extensions, and provided a general framework for testing composite hypotheses. In changepoint detection, he introduced new optimality criteria and computationally efficient procedures that remain influential. He applied these and related tools to problems in biostatistics. In this article, we review these key results in the broader context of sequential analysis.