<b>strucchange</b>: An<i>R</i>Package for Testing for Structural Change in Linear Regression Models

TLDR

The paper reviews structural‑change tests in linear regression from both generalized fluctuation and Chow test frameworks and proposes a unified implementation in the R package strucchange. The strucchange package implements these tests, offering functions to fit, plot, and evaluate empirical fluctuation processes (CUSUM, MOSUM, etc.) and sequences of F statistics (supF, aveF, expF), and supports monitoring of incoming data. These tools enable clear visualization of structural changes in regression relationships and robust assessment of their statistical significance.

Abstract

This paper reviews tests for structural change in linear regression models from the generalized fluctuation test framework as well as from the F test (Chow test) framework. It introduces a unified approach for implementing these tests and presents how these ideas have been realized in an R package called strucchange. Enhancing the standard significance test approach the package contains methods to fit, plot and test empirical fluctuation processes (like CUSUM, MOSUM and estimates-based processes) and to compute, plot and test sequences of F statistics with the supF , aveF and expF test. Thus, it makes powerful tools available to display information about structural changes in regression relationships and to assess their significance. Furthermore, it is described how incoming data can be monitored.