A B C D E G I L M N P Q R S U 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" |
| groupemomprior | Class "msPriorSpec" |
| groupimomprior | Class "msPriorSpec" |
| groupmomprior | Class "msPriorSpec" |
| groupzellnerprior | Class "msPriorSpec" |
| ic | Class "msPriorSpec" |
| icarplusprior | 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" |
| imomprior | Class "msPriorSpec" |
| localnulltest | Local variable selection |
| localnulltest_fda | Local variable selection |
| localnulltest_fda_givenknots | Local variable selection |
| localnulltest_givenknots | Local variable selection |
| marginalLikelihood | Marginal (or integrated) likelihood density of the observed data for an individual model handled by modelSelection (regression, GLM, GAM, accelerated failure time, regression with Normal, two-piece Normal, Laplace or two-piece Laplace residuals |
| 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 generalized linear and generalized additive models. |
| modelSelection | Bayesian variable selection for generalized linear and generalized additive models. |
| modelSelectionGGM | Bayesian variable selection for linear models via non-local priors. |
| modelSelection_eBayes | Bayesian variable selection for generalized linear and generalized additive models. |
| modelunifprior | Class "msPriorSpec" |
| momprior | Class "msPriorSpec" |
| 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" |
| 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. |
| 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. |
| 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 |
| zellnerprior | Class "msPriorSpec" |