misaem - Linear Regression and Logistic Regression with Missing Covariates
Estimate parameters of linear regression and logistic regression with missing covariates with missing data, perform model selection and prediction, using EM-type algorithms. Jiang W., Josse J., Lavielle M., TraumaBase Group (2020) <doi:10.1016/j.csda.2019.106907>.
Last updated 4 years ago
4.20 score 1 stars 32 scripts 756 downloadsdenoiseR - Regularized Low Rank Matrix Estimation
Estimate a low rank matrix from noisy data using singular values thresholding and shrinking functions. Impute missing values with matrix completion. The method is described in <arXiv:1602.01206>.
Last updated 5 years ago
1.72 score 52 scripts 197 downloads