Empirical Bayes Variable Selection via ICM/M Algorithm
Hyperparameter estimation for a and b.
Hyperparameter estimation for alpha.
Obtain a regression coefficient when assuming Ising prior (with struct...
Obtain model coefficient without assuming prior on structure of predic...
Obtain pseudodata based on the binary logistic regression model.
Obtain pseudodata based on the Cox's regression model.
Standard deviation estimation.
Estimate posterior probability of mixing weight.
Mixing weight estimation.
Local posterior probability estimation.
Local posterior probability estimation
Empirical Bayes Variable Selection via ICM/M
Empirical Bayes Variable Selection
Empirical Bayes variable selection via ICM/M algorithm for normal, binary logistic, and Cox's regression. The basic problem is to fit high-dimensional regression which sparse coefficients. This package allows incorporating the Ising prior to capture structure of predictors in the modeling process. More information can be found in the papers listed in the URL below.
Useful links