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.
|Author||Bochao Jia [aut, ctb, cre, cph], Faming Liang [ctb]|
|Maintainer||Bochao Jia <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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