Nonparametric Cusum Charts for Angular Data with Applications in Health Science and Astrophysics

TL;DR

This paper introduces non-parametric, rotation-invariant CUSUM charts designed to detect shifts in mean direction and concentration in angular data, with applications demonstrated in health science and astrophysics.

Contribution

It develops novel non-parametric CUSUM methods that are rotation-invariant for angular data, expanding change detection tools in directional statistics.

Findings

Theoretical properties of the CUSUMs are established.

Monte Carlo simulations validate the methods.

Applications demonstrate effectiveness in health and astrophysics data.

Abstract

This paper develops non-parametric rotation invariant CUSUMs suited to the detection of changes in the mean direction as well as changes in the concentration parameter of angular data. The properties of the CUSUMs are illustrated by theoretical calculations, Monte Carlo simulation and application to sequentially observed angular data from health science and astrophysics.