MixedDataImpute (0.1)

0 users

Missing Data Imputation for Continuous and Categorical Data using Nonparametric Bayesian Joint Models.

http://cran.r-project.org/web/packages/MixedDataImpute

Missing data imputation for continuous and categorical data, using nonparametric Bayesian joint models (specifically the hierarchically coupled mixture model with local dependence described in Murray and Reiter (2015); see 'citation("MixedDataImpute")' or http://arxiv.org/abs/1410.0438). See '?hcmm_impute' for example usage.

Maintainer: Jared S. Murray
Author(s): Jared S. Murray

License: GPL-3

Uses: gdata, Rcpp

Released about 3 years ago.


Ratings

Overall:

  (0 votes)

Documentation:

  (0 votes)

Log in to vote.

Reviews

No one has written a review of MixedDataImpute yet. Want to be the first? Write one now.


Related packages: Amelia, CVThresh, HardyWeinberg, Hmisc, ade4, cat, eigenmodel, experiment, ltm, memisc, mice, mitools, mix, norm, pan, randomForest, sbgcop, yaImpute, zoo, SNPassoc(20 best matches, based on common tags.)


Search for MixedDataImpute on google, google scholar, r-help, r-devel.

Visit MixedDataImpute on R Graphical Manual.