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bayesdistreg

An R package for Bayesian Distribution Regression. This package was first used for analyses in the paper "Bayesian Distribution Regression" by Weige Huang and Emmanuel Selorm Tsyawo. The paper is the recommended citation and reference for the package bayesdistreg. The package implements routines in the paper including the three Bayesian Distribution Regression estimators namely, the Non-asymptotic, Semi-Asymptotic, and Asymptotic BDR. Link to the package webpage https://estsyawo.github.io/bayesdistreg/

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Install

install.packages('bayesdistreg')

Monthly Downloads

219

Version

0.1.0

License

GPL-2

Maintainer

Emmanuel Tsyawo

Last Published

February 5th, 2019

Functions in bayesdistreg (0.1.0)

distreg

Bayesian distribution regression
distreg.asymp

Asymptotic distribution regression
parLply

Parallel compute
par_distreg

Parallel compute bayesian distribution regression
posterior

Posterior distribution
prior_n

Normal Prior distribution
IndepMH

Independence Metropolis-Hastings Algorithm
LogitLink

Logit function
distreg_cfa.sas

Semi-asymptotic counterfactual distribution
dr_asympar

Binary glm object at several threshold values
indicat

Indicator function
jdpar.asymp

Joint asymptotic mutivariate density of parameters
distreg.sas

Semi-asymptotic bayesian distribution
jntCBOM

Montiel Olea and Plagborg-Moller (2018) confidence bands
distreg_cfa

Counterfactual bayesian distribution regression
lapl_aprx2

Laplace approximation of posterior to normal
lapl_aprx

Laplace approximation of posterior to normal
logit

Logit likelihood function
prior_u

Uniform Prior distribution
simcnfB

Symmetric simultaneous bayesian confidence bands
quant_bdr

Quantile conversion of a bayesian distribution matrix
RWMH

Random Walk Metropolis-Hastings Algorithm
asymcnfB

Asymmetric simultaneous bayesian confidence bands
fitdist

The distribution of mean fitted logit probabilities
fitlogit

Fitted logit probabilities