Testing, Monitoring, and Dating Structural Changes

Testing, monitoring and dating structural changes in (linear) regression models. strucchange features tests/methods from the generalized fluctuation test framework as well as from the F test (Chow test) framework. This includes methods to fit, plot and test fluctuation processes (e.g., CUSUM, MOSUM, recursive/moving estimates) and F statistics, respectively. It is possible to monitor incoming data online using fluctuation processes. Finally, the breakpoints in regression models with structural changes can be estimated together with confidence intervals. Emphasis is always given to methods for visualizing the data.

Testing, Monitoring, and Dating Structural Changes

Overview

The R package strucchange provides a comprehensive toolbox for testing, monitoring, and dating structural changes in linear regression models. Many of the methods have also been generalized to any parametric model estimated by least squares, maximum likelihood, and other M-type estimators. In short, these methods are concerned with answering the following questions.

• Testing: Are the parameters of a model stable throughout the sample period or is there evidence that they changed over time?
• Monitoring: If a model with stable parameters could be established, do the parameters remain stable as new observations come in?
• Dating: If there is evidence for changes in the parameters, when and how did the parameters change?

Various families of tests are implemented, including the generalized fluctuation test framework as well as the $F$ test (or Chow test) framework. This includes methods to fit, plot and test fluctuation processes (e.g., CUSUM, MOSUM, recursive/moving estimates) and $F$ statistics, respectively.

Citations

Zeileis A, Leisch F, Hornik K, Kleiber C (2002). "strucchange: An R Package for Testing for Structural Change in Linear Regression Models." Journal of Statistical Software, 7(2), 1-38. doi:10.18637/jss.v007.i02

Zeileis A, Kleiber C, Krämer W, Hornik K (2003). "Testing and Dating of Structural Changes in Practice." Computational Statistics & Data Analysis, 44(1-2), 109-123. doi:10.1016/S0167-9473(03)00030-6

Zeileis A (2006). "Implementing a Class of Structural Change Tests: An Econometric Computing Approach." Computational Statistics & Data Analysis, 50(11), 2987-3008. doi:10.1016/j.csda.2005.07.001

Installation

The stable version of strucchange is available from CRAN:

install.packages("strucchange")

The latest development version can be installed from R-universe:

install.packages("strucchange", repos = "https://zeileis.R-universe.dev")

License

The package is available under the General Public License version 3 or version 2