rseg: recursive segmentation (rseg)

Recursive segmentation (rseg) makes use of recursive partitioning methods to perform exploratory subgroup analysis in an automated manner that resembles the patient rule induction method (PRIM). Therefore, tree models are fit to the data to identify subsets with outstanding outcome values. These are iteratively removed from the data which yields a sequence of subsets, called 'segments'.

Author
Alexander Hapfelmeier
Date of publication
2016-08-26 10:56:43
Maintainer
Alexander Hapfelmeier <Alexander.Hapfelmeier@tum.de>
License
GPL (>= 2)
Version
0.1.0

View on R-Forge

Man pages

aic
AIC and BIC guided aggregation of segments
cSeg
Recursive Segementation by Conditional Inference
eSeg
Recursive Segmentation by Evolutionary Learning
gettree
Extract tree model
plot.segmentation
Plot objects of class 'segmentation'
predict.segmentation
Predictions by recursive segmentation
print.segmentation
Print objects of class 'segmentation'
rSeg
Recursive Segmentation by CART
summary.segmentation
Summary of objects of class 'segmentation'

Files in this package

rseg/DESCRIPTION
rseg/NAMESPACE
rseg/R
rseg/R/aic_bic.R
rseg/R/cSeg.R
rseg/R/eSeg.R
rseg/R/gettree.R
rseg/R/plot.R
rseg/R/predict.R
rseg/R/print.R
rseg/R/rSeg.R
rseg/R/summary.R
rseg/man
rseg/man/aic.Rd
rseg/man/cSeg.Rd
rseg/man/eSeg.Rd
rseg/man/gettree.Rd
rseg/man/plot.segmentation.Rd
rseg/man/predict.segmentation.Rd
rseg/man/print.segmentation.Rd
rseg/man/rSeg.Rd
rseg/man/summary.segmentation.Rd