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Implements a Markov Chain Monte Carlo algorithm to approximate exact conditional inference for logistic regression models. Exact conditional inference is based on the distribution of the sufficient statistics for the parameters of interest given the sufficient statistics for the remaining nuisance parameters. Using model formula notation, users specify a logistic model and model terms of interest for exact inference. See Zamar et al. (2007) <doi:10.18637/jss.v021.i03> for more details.

Type Size Name Uploaded Downloads Labels
conda 549.7 kB | win-64/r-elrm-1.2.4-r36h796a38f_0.tar.bz2  5 years and 4 months ago 0 main
conda 546.5 kB | osx-64/r-elrm-1.2.4-r36h466af19_0.tar.bz2  5 years and 4 months ago 1 main
conda 540.2 kB | linux-64/r-elrm-1.2.4-r36h29659fb_0.tar.bz2  5 years and 4 months ago 0 main

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