Package: mimi 0.2.0

Genevieve Robin

mimi: Main Effects and Interactions in Mixed and Incomplete Data

Generalized low-rank models for mixed and incomplete data frames. The main function may be used for dimensionality reduction of imputation of numeric, binary and count data (simultaneously). Main effects such as column means, group effects, or effects of row-column side information (e.g. user/item attributes in recommendation system) may also be modelled in addition to the low-rank model. Geneviève Robin, Olga Klopp, Julie Josse, Éric Moulines, Robert Tibshirani (2018) <arxiv:1806.09734>.

Authors:Geneviève Robin

mimi_0.2.0.tar.gz
mimi_0.2.0.tar.gz(r-4.5-noble)mimi_0.2.0.tar.gz(r-4.4-noble)
mimi_0.2.0.tgz(r-4.4-emscripten)mimi_0.2.0.tgz(r-4.3-emscripten)
mimi.pdf |mimi.html✨
mimi/json (API)

# Install 'mimi' in R:

install.packages('mimi', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

acs2016 - Excerpt of the 2016 Public Use American Census Survey

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 8 scripts 197 downloads 1 mentions 3 exports 109 dependencies

Last updated 6 years agofrom:2cb9df09ae. Checks:OK: 1 NOTE: 1. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Dec 21 2024
R-4.5-linux	NOTE	Dec 21 2024

Exports:covmat cv.mimi mimi

Dependencies:abind backports base64enc boot broom bslib cachem car carData cli cluster codetools colorspace cowplot cpp11 crosstalk data.table Deriv digest doBy doParallel dplyr DT ellipse emmeans estimability evaluate FactoMineR fansi farver fastmap flashClust fontawesome foreach Formula fs generics ggplot2 ggrepel glmnet glue gtable highr htmltools htmlwidgets httpuv isoband iterators jquerylib jsonlite knitr labeling later lattice lazyeval leaps lifecycle lme4 magrittr MASS Matrix MatrixModels memoise mgcv microbenchmark mime minqa modelr multcompView munsell mvtnorm nlme nloptr nnet numDeriv pbkrtest pillar pkgconfig promises purrr quantreg R6 rappdirs rARPACK RColorBrewer Rcpp RcppEigen rlang rmarkdown RSpectra sass scales scatterplot3d shape softImpute SparseM stringi stringr survival tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun yaml

Help page	Topics
Excerpt of the 2016 Public Use American Census Survey (Alabama only)	acs2016
construct covariate matrix (predictor matrix) in the right format for input to the mimi or cv.mimi functions from tables of attributes about the rows or columns of data frames.	covmat
selection of the regularization parameters (lambda1 and lambda2) of the mimi function by cross-validation	cv.mimi
main function: low-rank models to analyze and impute mixed and incomplete data frames with numeric, binary and discrete variables, and missing values	mimi

Package: mimi 0.2.0

mimi: Main Effects and Interactions in Mixed and Incomplete Data

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)