Package: IROmiss
Type: Package
Title: Imputation Regularized Optimization Algorithm
Version: 1.0.0
Date: 2018-01-16
Authors@R: c(person("Bochao", "Jia", role = c("aut", "cre", "cph"), email = "jbc409@ufl.edu"),
  person("Faming", "Liang", role = c("ctb"), email = "fmliang@purdue.edu"))
Depends: R (>= 3.0.2)
Imports: mvtnorm, equSA, huge, ncvreg
Description: Missing data are frequently encountered in high-dimensional data analysis, but they are usually difficult to deal with using standard algorithms, such as the EM algorithm and its variants. This package provides a general algorithm, the so-called Imputation Regularized Optimization (IRO) algorithm, for high-dimensional missing data problems. You can refer to Liang, F., Jia, B., Xue, J., Li, Q. and Luo, Y. (2018) at <https://people.clas.ufl.edu/yeluo/files/ica10.pdf> for detail. The publication "An Imputation Regularized Optimization Algorithm for High-Dimensional Missing Data Problems and Beyond" will be appear on Journal of the Royal Statistical Society Series B soon.
License: GPL-2
LazyLoad: true
Packaged: 2018-01-17 14:13:13 UTC; jia97
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2018-01-17 16:35:16 UTC
RoxygenNote: 6.0.1
Author: Bochao Jia [aut, cre, cph],
  Faming Liang [ctb]
Maintainer: Bochao Jia <jbc409@ufl.edu>
