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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.
| Version: | 1.0.1 |
| Depends: | R (≥ 3.4.0) |
| Imports: | ggplot2, reshape2, LaplacesDemon, rlang, Rcpp, MASS, truncnorm |
| LinkingTo: | Rcpp, RcppArmadillo, RcppDist |
| Suggests: | mice, clusterGeneration |
| Published: | 2022-07-06 |
| Author: | Hesen Li |
| Maintainer: | Hesen Li <li.hesen.21 at gmail.com> |
| BugReports: | https://github.com/hli226/mvnimpute/issues |
| License: | GPL-2 | GPL-3 |
| URL: | https://github.com/hli226/mvnimpute |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | mvnimpute results |
| Reference manual: | mvnimpute.pdf |
| Package source: | mvnimpute_1.0.1.tar.gz |
| Windows binaries: | r-devel: mvnimpute_1.0.1.zip, r-release: mvnimpute_1.0.1.zip, r-oldrel: mvnimpute_1.0.1.zip |
| macOS binaries: | r-release (arm64): mvnimpute_1.0.1.tgz, r-oldrel (arm64): mvnimpute_1.0.1.tgz, r-release (x86_64): mvnimpute_1.0.1.tgz, r-oldrel (x86_64): mvnimpute_1.0.1.tgz |
| Old sources: | mvnimpute archive |
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