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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.
Package details |
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Author | Bochao Jia [aut, ctb, cre, cph], Faming Liang [ctb] |
Maintainer | Bochao Jia <jbc409@ufl.edu> |
License | GPL-2 |
Version | 1.0.2 |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
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