sambia
A Collection of Techniques Correcting for Sample Selection Bias
A collection of various techniques correcting statistical models for sample selection bias is provided. In particular, the resampling-based methods "stochastic inverse-probability oversampling" and "parametric inverse-probability 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)
- Version0.1.0
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release06/06/2018
Team
Norbert Krautenbacher
Norbert Krautenbacher, Kevin Strauss, Maximilian Mandl, Christiane Fuchs
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- Imports8 packages