mvnimpute
Simultaneously Impute the Missing and Censored Values
Implementing a multiple imputation algorithm for multivariate data with missing and censored values under a coarsening at random assumption (Heitjan and Rubin, 1991<doi:10.1214/aos/1176348396>). The multiple imputation algorithm is based on the data augmentation algorithm proposed by Tanner and Wong (1987)<doi:10.1080/01621459.1987.10478458>. The Gibbs sampling algorithm is adopted to to update the model parameters and draw imputations of the coarse data.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.1 |
rolling linux/jammy R-4.5 | mvnimpute_1.0.1.tar.gz |
450.7 KiB |
1.0.1 |
rolling linux/noble R-4.5 | mvnimpute_1.0.1.tar.gz |
452.8 KiB |
1.0.1 |
rolling source/ R- | mvnimpute_1.0.1.tar.gz |
256.1 KiB |
1.0.1 |
latest linux/jammy R-4.5 | mvnimpute_1.0.1.tar.gz |
450.7 KiB |
1.0.1 |
latest linux/noble R-4.5 | mvnimpute_1.0.1.tar.gz |
452.8 KiB |
1.0.1 |
latest source/ R- | mvnimpute_1.0.1.tar.gz |
256.1 KiB |
1.0.1 |
2026-04-26 source/ R- | mvnimpute_1.0.1.tar.gz |
256.1 KiB |
1.0.1 |
2026-04-23 source/ R- | mvnimpute_1.0.1.tar.gz |
256.1 KiB |
1.0.1 |
2026-04-09 windows/windows R-4.5 | mvnimpute_1.0.1.zip |
772.2 KiB |
1.0.1 |
2025-04-20 source/ R- | mvnimpute_1.0.1.tar.gz |
256.1 KiB |