Package: IROmiss
Type: Package
Title: Imputation Regularized Optimization Algorithm
Version: 1.0.2
Date: 2020-02-19
Authors@R: c(person("Bochao", "Jia", role = c("aut", "ctb", "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 <arXiv:1802.02251> for detail.
License: GPL-2
LazyLoad: true
Packaged: 2020-02-19 01:41:39 UTC; jia97
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2020-02-19 05:10:02 UTC
RoxygenNote: 6.0.1
Author: Bochao Jia [aut, ctb, cre, cph],
  Faming Liang [ctb]
Maintainer: Bochao Jia <jbc409@ufl.edu>
