Add to ORKGDescription 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 pro-cesses (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. LazyData yes Depends R (> = 2.10.0), zoo, sandwic
Some results on testing for changes in generalized linear models are presented and approximations to...
This paper extends the classical Chow (1960) test for structural change in linear regression models ...
This paper considers the linear regression model with the lagged dependent variable as a regressor. ...
This paper introduces ideas and methods for testing for structural change in linear regression model...
This introduction to the R package strucchange is a (slightly) modified version of the paper of Zeil...
This paper investigates the problem of testing for structural change for diagnostic purposes. We pro...
The classical approach to testing for structural change employs retrospective tests using a historic...
The classical approach to testing for structural change employs retrospective tests using a historic...
We propose a nonparametric approach to the estimation and testing of structural change in time serie...
The paper presents an approach to the analysis of data that contains (multiple) structural changes i...
The implementation of a recently suggested class of structural change tests, which test for paramete...
Over the last years, several structural change tests have been extended to monitoring of linear regr...
A unified toolbox for testing, monitoring, and dating structural changes is provided for likelihood-...
summary:Regression and scale invariant $M$-test procedures are developed for detection of structural...
The paper presents an approach to the analysis of data that contains (multiple) structural changes i...
Some results on testing for changes in generalized linear models are presented and approximations to...
This paper extends the classical Chow (1960) test for structural change in linear regression models ...
This paper considers the linear regression model with the lagged dependent variable as a regressor. ...
This paper introduces ideas and methods for testing for structural change in linear regression model...
This introduction to the R package strucchange is a (slightly) modified version of the paper of Zeil...
This paper investigates the problem of testing for structural change for diagnostic purposes. We pro...
The classical approach to testing for structural change employs retrospective tests using a historic...
The classical approach to testing for structural change employs retrospective tests using a historic...
We propose a nonparametric approach to the estimation and testing of structural change in time serie...
The paper presents an approach to the analysis of data that contains (multiple) structural changes i...
The implementation of a recently suggested class of structural change tests, which test for paramete...
Over the last years, several structural change tests have been extended to monitoring of linear regr...
A unified toolbox for testing, monitoring, and dating structural changes is provided for likelihood-...
summary:Regression and scale invariant $M$-test procedures are developed for detection of structural...
The paper presents an approach to the analysis of data that contains (multiple) structural changes i...
Some results on testing for changes in generalized linear models are presented and approximations to...
This paper extends the classical Chow (1960) test for structural change in linear regression models ...
This paper considers the linear regression model with the lagged dependent variable as a regressor. ...