Model Selection with Bayesian Methods and Information Criteria

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Documentation for package ‘mombf’ version 3.5.4

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

Help Pages

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

-- A --

aic	Class "msPriorSpec"

-- B --

bbPrior	Priors on model space for variable selection problems
bestAIC	Model with best AIC, BIC, EBIC or other general information criteria (getIC)
bestBIC	Model with best AIC, BIC, EBIC or other general information criteria (getIC)
bestEBIC	Model with best AIC, BIC, EBIC or other general information criteria (getIC)
bestIC	Model with best AIC, BIC, EBIC or other general information criteria (getIC)
bfnormmix	Number of Normal mixture components under Normal-IW and Non-local priors
bic	Class "msPriorSpec"
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 --

emomprior	Class "msPriorSpec"
eprod	Expectation of a product of powers of Normal or T random variables
exponentialprior	Class "msPriorSpec"

-- G --

getAIC	Obtain AIC, BIC, EBIC or other general information criteria (getIC)
getAIC-method	Obtain AIC, BIC, EBIC or other general information criteria (getIC)
getAIC-methods	Obtain AIC, BIC, EBIC or other general information criteria (getIC)
getBIC	Obtain AIC, BIC, EBIC or other general information criteria (getIC)
getBIC-method	Obtain AIC, BIC, EBIC or other general information criteria (getIC)
getBIC-methods	Obtain AIC, BIC, EBIC or other general information criteria (getIC)
getEBIC	Obtain AIC, BIC, EBIC or other general information criteria (getIC)
getEBIC-method	Obtain AIC, BIC, EBIC or other general information criteria (getIC)
getEBIC-methods	Obtain AIC, BIC, EBIC or other general information criteria (getIC)
getIC	Obtain AIC, BIC, EBIC or other general information criteria (getIC)
getIC-method	Obtain AIC, BIC, EBIC or other general information criteria (getIC)
getIC-methods	Obtain AIC, BIC, EBIC or other general information criteria (getIC)
groupemomprior	Class "msPriorSpec"
groupimomprior	Class "msPriorSpec"
groupmomprior	Class "msPriorSpec"
groupzellnerprior	Class "msPriorSpec"

-- H --

hald

Hald Data

-- I --

ic	Class "msPriorSpec"
icfit	Class "icfit"
icfit-class	Class "icfit"
icfit.coef	Class "icfit"
icfit.predict	Class "icfit"
icfit.summary	Class "icfit"
icov	Extract estimated inverse covariance
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 and inverse moment priors
imomprior	Class "msPriorSpec"
imomunknown	Bayes factors for moment and inverse moment priors

-- L --

localnulltest	Local variable selection
localnulltest_fda	Local variable selection
localnulltest_fda_givenknots	Local variable selection
localnulltest_givenknots	Local variable selection

-- 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.
modelSelectionGGM	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 and inverse moment priors
momprior	Class "msPriorSpec"
momunknown	Bayes factors for moment and inverse moment priors
msfit	Class "msfit"
msfit-class	Class "msfit"
msfit.coef	Class "msfit"
msfit.plot	Class "msfit"
msfit.predict	Class "msfit"
msfit_ggm	Class "msfit_ggm"
msfit_ggm-class	Class "msfit_ggm"
msfit_ggm.coef	Class "msfit_ggm"
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
plotprior	Plot estimated marginal prior inclusion probabilities
plotprior-method	Plot estimated marginal prior inclusion probabilities
plotprior-methods	Plot estimated marginal prior inclusion probabilities
pmom	Non-local prior density, cdf and quantile functions.
pmomigmarg	Non-local prior density, cdf and quantile functions.
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
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
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 "icfit"
show-method	Class "mixturebf"
show-method	Class "msfit"
show-method	Class "msfit_ggm"

-- U --

unifPrior

Priors on model space for variable selection problems

-- X --

x.hald

Hald Data

-- Y --

y.hald

Hald Data

-- Z --

zellnerprior

Class "msPriorSpec"