Testing, Monitoring, and Dating Structural Changes: C++ Version
Boundary for Empirical Fluctuation Processes
Boundary for F Statistics
Boundary Function for Monitoring of Structural Changes
Boundary Function for Structural Change Tests
Breakdates Corresponding to Breakpoints
Factor Coding of Segmentations
Dating Breaks
Generators for efpFunctionals along Categorical Variables
Confidence Intervals for Breakpoints
Empirical Fluctuation Processes
Functionals for Fluctuation Processes
F Statistics
Generalized Empirical M-Fluctuation Processes
Log Likelihood and Information Criteria for Breakpoints
Magnitudes of Breakpoints
Monitoring of Empirical Fluctuation Processes
Plot Empirical Fluctuation Process
Plot F Statistics
Plot Methods for mefp Objects
Recursive Residuals
Root of X^TX
Root of a Matrix
Structural Change Tests in Parametric Models
Generalized Fluctuation Tests
Structural Change Tests in Linear Regression Models
supF-, aveF- and expF-Test
Structural Change Tests
Inversion of X'X
Internal strucchange objects
Generators for efpFunctionals along Continuous Variables
A fast implementation with additional experimental features for testing, monitoring and dating structural changes in (linear) regression models. 'strucchangeRcpp' 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. cumulative/moving sum, recursive/moving estimates) and F statistics, respectively. These methods are described in Zeileis et al. (2002) <doi:10.18637/jss.v007.i02>. Finally, the breakpoints in regression models with structural changes can be estimated together with confidence intervals, and their magnitude as well as the model fit can be evaluated using a variety of statistical measures.
Useful links