A B C D E G H I L M N P Q R S U X Y Z
aic | Class "msPriorSpec" |
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 |
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 |
exponentialprior | Class "msPriorSpec" |
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" |
hald | Hald Data |
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 |
localnulltest | Local variable selection |
localnulltest_fda | Local variable selection |
localnulltest_fda_givenknots | Local variable selection |
localnulltest_givenknots | Local variable selection |
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" |
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 "icfit" |
show-method | Class "mixturebf" |
show-method | Class "msfit" |
show-method | Class "msfit_ggm" |
unifPrior | Priors on model space for variable selection problems |
x.hald | Hald Data |
y.hald | Hald Data |
zellnerprior | Class "msPriorSpec" |