# Bayesian Model Selection and Averaging for Non-Local and Local Priors

## Documentation for package ‘mombf’ version 3.1.3

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

B C D E G H I M N P Q R S U X Y Z

## -- B --

bbPrior | Priors on model space for variable selection problems
bfnormmix | Number of Normal mixture components under Normal-IW and Non-local priors
bicprior | Class "msPriorSpec"
binomPrior | Priors on model space for variable selection problems

## -- C --

cil | Treatment effect estimation for linear models via Confounder Importance Learning using non-local priors.
coef.mixturebf | Class "mixturebf"
coefByModel | Class "msfit"
coefByModel-method | Class "msfit"
coefByModel-methods | Class "msfit"

## -- D --

dalapl | Density and random draws from the asymmetric Laplace distribution
ddir | Dirichlet density
demom | Non-local prior density, cdf and quantile functions.
demom-method | Non-local prior density, cdf and quantile functions.
demom-methods | Non-local prior density, cdf and quantile functions.
demomigmarg | Non-local prior density, cdf and quantile functions.
dimom | Non-local prior density, cdf and quantile functions.
diwish | Density for Inverse Wishart distribution
dmom | Non-local prior density, cdf and quantile functions.
dmomigmarg | Non-local prior density, cdf and quantile functions.
dpostNIW | Posterior Normal-IWishart density

## -- E --

emomLM | Bayesian variable selection and model averaging for linear and probit models via non-local priors.
emomPM | Bayesian variable selection and model averaging for linear and probit models via non-local priors.
emomprior | Class "msPriorSpec"
eprod | Expectation of a product of powers of Normal or T random variables

## -- G --

getBIC | Obtain BIC and EBIC
getBIC-method | Obtain BIC and EBIC
getBIC-methods | Obtain BIC and EBIC
getEBIC | Obtain BIC and EBIC
getEBIC-method | Obtain BIC and EBIC
getEBIC-methods | Obtain BIC and EBIC
groupemomprior | Class "msPriorSpec"
groupimomprior | Class "msPriorSpec"
groupmomprior | Class "msPriorSpec"
groupzellnerprior | Class "msPriorSpec"

## -- H --

hald | Hald Data

## -- I --

igprior | Class "msPriorSpec"
imombf | Moment and inverse moment Bayes factors for linear models.
imombf.lm | Moment and inverse moment Bayes factors for linear models.
imomknown | Bayes factors for moment, inverse moment and Zellner-Siow g-prior.
imomprior | Class "msPriorSpec"
imomunknown | Bayes factors for moment, inverse moment and Zellner-Siow g-prior.

## -- M --

marginalNIW | Marginal likelihood under a multivariate Normal likelihood and a conjugate Normal-inverse Wishart prior.
marginalNIW-method | Marginal likelihood under a multivariate Normal likelihood and a conjugate Normal-inverse Wishart prior.
marginalNIW-methods | Marginal likelihood under a multivariate Normal likelihood and a conjugate Normal-inverse Wishart prior.
mixturebf | Class "mixturebf"
mixturebf-class | Class "mixturebf"
modelbbprior | Class "msPriorSpec"
modelbinomprior | Class "msPriorSpec"
modelcomplexprior | Class "msPriorSpec"
modelsearchBlockDiag | Bayesian variable selection for linear models via non-local priors.
modelSelection | Bayesian variable selection for linear models via non-local priors.
modelunifprior | Class "msPriorSpec"
mombf | Moment and inverse moment Bayes factors for linear models.
mombf.lm | Moment and inverse moment Bayes factors for linear models.
momknown | Bayes factors for moment, inverse moment and Zellner-Siow g-prior.
momprior | Class "msPriorSpec"
momunknown | Bayes factors for moment, inverse moment and Zellner-Siow g-prior.
msfit | Class "msfit"
msfit-class | Class "msfit"
msfit.coef | Class "msfit"
msfit.predict | Class "msfit"
msPriorSpec | Class "msPriorSpec"
msPriorSpec-class | Class "msPriorSpec"

## -- N --

nlpMarginal | Marginal density of the observed data for linear regression with Normal, two-piece Normal, Laplace or two-piece Laplace residuals under non-local and Zellner priors
nlpmarginals | Marginal density of the observed data for linear regression with Normal, two-piece Normal, Laplace or two-piece Laplace residuals under non-local and Zellner priors
normalidprior | Class "msPriorSpec"

## -- P --

palapl | Density and random draws from the asymmetric Laplace distribution
pemom | Non-local prior density, cdf and quantile functions.
pemomigmarg | Non-local prior density, cdf and quantile functions.
pimom | Non-local prior density, cdf and quantile functions.
pimomMarginalK | Marginal density of the observed data for linear regression with Normal, two-piece Normal, Laplace or two-piece Laplace residuals under non-local and Zellner priors
pimomMarginalU | Marginal density of the observed data for linear regression with Normal, two-piece Normal, Laplace or two-piece Laplace residuals under non-local and Zellner priors
pmom | Non-local prior density, cdf and quantile functions.
pmomigmarg | Non-local prior density, cdf and quantile functions.
pmomLM | Bayesian variable selection and model averaging for linear and probit models via non-local priors.
pmomMarginalK | Marginal density of the observed data for linear regression with Normal, two-piece Normal, Laplace or two-piece Laplace residuals under non-local and Zellner priors
pmomMarginalU | Marginal density of the observed data for linear regression with Normal, two-piece Normal, Laplace or two-piece Laplace residuals under non-local and Zellner priors
pmomPM | Bayesian variable selection and model averaging for linear and probit models via non-local priors.
postModeBlockDiag | Bayesian model selection and averaging under block-diagonal X'X for linear models.
postModeOrtho | Bayesian model selection and averaging under block-diagonal X'X for linear models.
postProb | Obtain posterior model probabilities
postProb-method | Obtain posterior model probabilities
postProb-methods | Obtain posterior model probabilities
postSamples | Extract posterior samples from an object
postSamples-method | Extract posterior samples from an object
postSamples-methods | Extract posterior samples from an object
pplPM | Bayesian variable selection and model averaging for linear and probit models via non-local priors.
ppmodel | Bayesian variable selection and model averaging for linear and probit models via non-local priors.
priorp2g | Moment and inverse moment prior elicitation

## -- Q --

qimom | Non-local prior density, cdf and quantile functions.
qmom | Non-local prior density, cdf and quantile functions.

## -- R --

ralapl | Density and random draws from the asymmetric Laplace distribution
rnlp | Posterior sampling for regression parameters
rnlp-method | Posterior sampling for regression parameters
rnlp-methods | Posterior sampling for regression parameters
rpostNIW | Posterior Normal-IWishart density

## -- S --

show-method | Class "mixturebf"
show-method | Class "msfit"

## -- U --

unifPrior | Priors on model space for variable selection problems

## -- X --

x.hald | Hald Data

## -- Y --

y.hald | Hald Data

## -- Z --

zbfknown | Bayes factors for moment, inverse moment and Zellner-Siow g-prior.
zbfunknown | Bayes factors for moment, inverse moment and Zellner-Siow g-prior.
zellnerbf | Moment and inverse moment Bayes factors for linear models.
zellnerbf.lm | Moment and inverse moment Bayes factors for linear models.
zellnerprior | Class "msPriorSpec"