The modal age of Statistics

TL;DR

This paper surveys recent advances in mode estimation, highlighting its applications in classical statistical tasks like clustering and regression, and explores its broader implications across various fields.

Contribution

It provides an extensive review of traditional mode estimation methods and discusses the impact of modern modal approaches on diverse statistical problems.

Findings

Modern modal methods offer new solutions to classical statistical tasks.

Applying modal techniques broadens the scope of statistical inference.

The survey highlights the versatility of mode-based approaches across fields.

Abstract

Recently, a number of statistical problems have found an unexpected solution by inspecting them through a "modal point of view". These include classical tasks such as clustering or regression. This has led to a renewed interest in estimation and inference for the mode. This paper offers an extensive survey of the traditional approaches to mode estimation and explores the consequences of applying this modern modal methodology to other, seemingly unrelated, fields.