Package: MIHD
Type: Package
Title: Multiple Imputation in the Presence of High-dimensinal Data
Version: 3.0
Date: 2015-09-22
Author: Yi Deng and Qi Long
Maintainer: Yi Deng <ydeng26@emory.edu>
Depends: MASS, glmnet, mice, blasso
Description: Multiple imputation through direct use of regularized regression
    (DURR) and indirect use of regularized regression (IURR), as well as
    Bayesian Lasso Regression for dataset with one single variable partially observed in the presence of high-dimensional data. This package can also conduct multiple imputations for general missing pattern. Built-in imputation models are provided for
    continuous data (normal linear regression), binary data (logistic
    regression) and poisson data (log-linear regression).
License: GPL-2|GPL-3
Built: R 3.2.1; ; 2015-09-30 00:13:10 UTC; windows
