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R-BPHO - Bayesian Prediction with High-order Interactions

Description:

This software can be used in two situations. The first is to predict the
next outcome based on the previous states of a discrete sequence. The
second is to classify a discrete response based on a number of discreate
covariates. In both situations, we use Bayesian logistic regression models
that consider the high-order interactions. The models are trained with
slice sampling method, a variant of Markov chain Monte Carlo. The time
arising from using high-order interactions is reduced greatly by our
compression technique that represents a group of original parameters as a
single one in MCMC
step.

Packages

- initial package for Fedora

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