The package uses fitting axesaligned rectangles to a time series in order to find structural breaks. The algorithm enclose the time series in a number of axesaligned rectangles and tries to minimize their area and number. As these are conflicting aims, the user has to specify a parameter alpha in [0.0,1.0]. Values close to 0 result in more breakpoints, values close to 1 in fewer. The left edges of the rectangles are the breakpoints. The package supplies two methods, computeBreakPoints(series,alpha) which returns the indices of the break points and computeRectangles(series,alpha) which returns the rectangles. The algorithm is randomised; it uses a genetic algorithm. Therefore, the break point sequence found can be different in different executions of the method on the same data, especially when used on longer series of some thousand observations. The algorithm uses a rangetree as background data structure which makes i very fast and suited to analyse series with millions of observations. A detailed description can be found in Paul Fischer, Astrid Hilbert, Fast detection of structural breaks, Proceedings of Compstat 2014.
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Author  Paul Fischer [aut, cre, cph], Astrid Hilbert [ctb, cph] 
Date of publication  20140720 21:17:32 
Maintainer  Paul Fischer <pafi@dtu.dk> 
License  GPL2 
Version  0.26 
URL  http://www2.imm.dtu.dk/~pafi/StructBreak/index.html 
Package repository  View on CRAN 
Installation  Install the latest version of this package by entering the following in R:

Man pages  

computeBreakPoints: Structural break detection with rectangles  
computeRectangels: Structural break detection with rectangles 
Functions  

computeBreakPoints  Man page Source code 
computeRectangles  Man page Source code 
onLoad  Source code 
Files  

inst
 
inst/java
 
inst/java/sbrect_jr.jar
 
NAMESPACE
 
R
 
R/onLoad.R  
R/computeRectangles.R  
R/computeBreakPoints.R  
MD5
 
DESCRIPTION
 
man
 
man/computeBreakPoints.Rd  
man/computeRectangels.Rd 
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