A collection of various techniques correcting statistical models for sample selection bias is provided. In particular, the resamplingbased methods "stochastic inverseprobability oversampling" and "parametric inverseprobability bagging" are placed at the disposal which generate synthetic observations for correcting classifiers for biased samples resulting from stratified random sampling. For further information, see the article Krautenbacher, Theis, and Fuchs (2017) <doi:10.1155/2017/7847531>. The methods may be used for further purposes where weighting and generation of new observations is needed.
Package details 


Author  Norbert Krautenbacher, Kevin Strauss, Maximilian Mandl, Christiane Fuchs 
Maintainer  Norbert Krautenbacher <norbert.krautenbacher@tum.de> 
License  GPL3 
Version  0.1.0 
Package repository  View on CRAN 
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