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


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Documentation for package ‘mombf’ version 3.2.0

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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
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"
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
emomprior Class "msPriorSpec"
eprod Expectation of a product of powers of Normal or T random variables
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"
hald Hald Data
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
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 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.predict Class "msfit"
msPriorSpec Class "msPriorSpec"
msPriorSpec-class Class "msPriorSpec"
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"
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
qimom Non-local prior density, cdf and quantile functions.
qmom Non-local prior density, cdf and quantile functions.
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
show-method Class "mixturebf"
show-method Class "msfit"
unifPrior Priors on model space for variable selection problems
x.hald Hald Data
y.hald Hald Data
zellnerprior Class "msPriorSpec"