Bivariate change point detection: Joint detection of changes in expectation and variance

Abstract A method for change point detection is proposed. We consider a univariate sequence of independent random variables with piecewise constant expectation and variance, apart from which the distribution may vary periodically. aim to detect points in both variance. For that, we propose statistical test null hypothesis no an algorithm detection. Both are based on bivariate moving sum approach that jointly evaluates mean empirical The joint consideration helps improve inference compared separate approaches. infer strength type changes confidence. Nonparametric methodology supports analysis diverse data. Additionally, multiscale addresses complex patterns effects. demonstrate performance through theoretical results simulation studies. companion R ‐package jcp (available CRAN) discussed.