Packaged: 2016-09-05 22:53:23 UTC; michelballings

Title: Imputation Methods for Multivariate Multinomial Data
Authors@R: person("Alex", "Whitworth", , "whitworth.alex@gmail.com", c("aut", "cre"))
Description: Implements imputation methods using EM and Data Augmentation for
multinomial data following the work of Schafer 1997 <ISBN: 978-0-412-04061-0>.
Imports: gtools (>= 3.3), methods, parallel, Rcpp
Packaged: 2016-05-05 15:34:54 UTC; awhitworth

Packaged: 2016-05-25 17:41:35 UTC; awhitworth

Imports: gtools (>= 3.3), methods, parallel, Rcpp, DBI (>= 0.4),
Packaged: 2016-06-07 17:00:49 UTC; awhitworth

Packaged: 2016-06-15 23:41:56 UTC; awhitworth

Packaged: 2016-07-21 23:02:32 UTC; awhitworth

Packaged: 2016-08-09 15:51:40 UTC; awhitworth

Packaged: 2016-08-11 15:45:23 UTC; awhitworth

Imports: gtools (>= 3.3), methods, parallel, Rcpp (>= 0.11.4),
Packaged: 2021-12-02 01:53:48 UTC; awhitworth

Title: Impute Missing Data in Time Series Data with PSF Based Method
Description: Imputes the missing values in time series data with PSF algorithm based approach.
The details about PSF algorithm are available at:

Title: A General Imputation Framework in R
Description: This package provides a general imputation framework based on
variable selection methods including regularisation methods,
tree-based models and dimension reduction methods.
Imports: caret, reshape2, glmnet, pls, rda, Cubist, ridge, gbm, mboost,

Author: Lingbing Feng, Steffen Moritz, Gen Nowak, Alan. H. Welsh, Terry. J. O'Neill
Description: General imputation framework based on

Title: A General Multivariate Imputation Framework
person("Steffen", "Moritz", email="steffen.moritz10@gmail.com", role=c("aut", "cre"), comment = c(ORCID = "0000-0002-0085-1804")),person("Lingbing", "Feng", role=c("aut")),person("Gen", "Nowak", role=c("ctb")),person("Alan. H.", "Welsh", role=c("ctb")),person("Terry. J.", "O'Neill", role=c("ctb"))
Author: Steffen Moritz [aut, cre] (<https://orcid.org/0000-0002-0085-1804>),
Description: Multivariate Expectation-Maximization (EM) based imputation framework that offers several different algorithms. These include regularisation methods like Lasso and Ridge regression, tree-based models and dimensionality reduction methods like PCA and PLS.
Imports: stats, utils, graphics, reshape2
Suggests: testthat, rda, caret, glmnet, pls, Cubist, ridge, gbm,