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 |
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 |
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 |
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, inverse moment and Zellner-Siow g-prior. |
imomprior |
Class "msPriorSpec" |
imomunknown |
Bayes factors for moment, inverse moment and Zellner-Siow g-prior. |
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" |
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 |
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 |
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 |
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" |