Man pages for icmm
Empirical Bayes Variable Selection via ICM/M Algorithm
| get.ab | Hyperparameter estimation for 'a' and 'b'. |
| get.alpha | Hyperparameter estimation for 'alpha'. |
| get.beta | Obtain model coefficient without assuming prior on structure... |
| get.beta.ising | Obtain a regression coefficient when assuming Ising prior... |
| get.pseudodata.binomial | Obtain pseudodata based on the binary logistic regression... |
| get.pseudodata.cox | Obtain pseudodata based on the Cox's regression model. |
| get.sigma | Standard deviation estimation. |
| get.wpost | Estimate posterior probability of mixing weight. |
| get.wprior | Mixing weight estimation. |
| get.zeta | Local posterior probability estimation |
| get.zeta.ising | Local posterior probability estimation. |
| icmm | Empirical Bayes Variable Selection |
| icmm-package | Empirical Bayes Variable Selection via ICM/M |
| initbetaBinomial | Initial values for the regression coefficients used in... |
| initbetaCox | Initial values for the regression coefficients used in... |
| initbetaGaussian | Initial values for the regression coefficients used in... |
| linearrelation | Linear structure of predictors |
| simBinomial | Simulated data from the binary logistic regression model |
| simCox | Simulated data from Cox's regression model |
| simGaussian | Simulated data from the normal linear regression model |
