Implements Bayesian Distribution Regression methods. This package contains functions for three estimators (nonasymptotic, semiasymptotic and asymptotic) and related routines for Bayesian Distribution Regression in Huang and Tsyawo (2018) <doi:10.2139/ssrn.3048658> which is also the recommended reference to cite for this package. The functions can be grouped into three (3) categories. The first computes the logit likelihood function and posterior densities under uniform and normal priors. The second contains Independence and Random Walk MetropolisHastings Markov Chain Monte Carlo (MCMC) algorithms as functions and the third category of functions are useful for semiasymptotic and asymptotic Bayesian distribution regression inference.
Package details 


Author  Emmanuel Tsyawo [aut, cre], Weige Huang [aut] 
Maintainer  Emmanuel Tsyawo <estsyawo@temple.edu> 
License  GPL2 
Version  0.1.0 
Package repository  View on CRAN 
Installation 
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