bin2int

a Boolean/binary vector of length p representing
    a model

model

Takes a binary string representation of a model and
  converts to an integer

regression

Package for Bayesian Model Averaging in linear models and
	     generalized linear models using stochastic or
	     deterministic sampling without replacement from posterior
	     distributions.  Prior distributions on coefficients are
	     from Zellner's g-prior or mixtures of g-priors
	     corresponding to the Zellner-Siow Cauchy Priors or the
	     mixture of g-priors from 
	     Liang et al (2008)
	     <http://dx.doi.org/10.1198/016214507000001337>
	     for linear models or mixtures of
	     g-priors in GLMs of Li and Clyde (2015)
	     <http://arxiv.org/abs/1503.06913 >. Other model
	     selection criteria include AIC and BIC. Sampling
	     probabilities may be updated based on the sampled models
	     using Sampling w/out Replacement or an MCMC algorithm
	     samples models using the BAS tree structure as an efficient
	     hash table. Allows uniform or beta-binomial prior distributions on
	     models and for large p truncated priors on the model
	     space.  The user may force variables to always be included.

bin2int: Convert binary model representation into an integer

Description

Usage

Arguments

Value

Details