Package: mvnimpute 1.0.1

Hesen Li

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.

Authors:Hesen Li

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mvnimpute.pdf |mvnimpute.html
mvnimpute/json (API)

# Install 'mvnimpute' in R:
install.packages('mvnimpute', repos = c('https://hli226.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/hli226/mvnimpute/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • NHANES.dat - Combined NHANES dataset from 1999-2004 NHANES study
  • simulated.dat - Simulated continuous data with missing and censored values

On CRAN:

7 exports 0.62 score 37 dependencies 132 downloads

Last updated 2 years agofrom:87f644e9ee. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 03 2024
R-4.5-win-x86_64OKSep 03 2024
R-4.5-linux-x86_64OKSep 03 2024
R-4.4-win-x86_64OKSep 03 2024
R-4.4-mac-x86_64OKSep 03 2024
R-4.4-mac-aarch64OKSep 03 2024
R-4.3-win-x86_64OKSep 03 2024
R-4.3-mac-x86_64OKSep 03 2024
R-4.3-mac-aarch64OKSep 03 2024

Exports:acf.calcavg.plotconv.plotdata.generationmarg.plotmultiple.imputationvisual.plot

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelingLaplacesDemonlatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloRcppDistreshape2rlangscalesstringistringrtibbletruncnormutf8vctrsviridisLitewithr