Пакунок: r-cran-mice (3.13.0-2)

[ Source: r-cran-mice  ]

GNU R multivariate imputation by chained equations

Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in Van Buuren and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.

Інші пакунки пов'язані з r-cran-mice

• dep: libc6 (>= 2.4)

  Бібліотека GNU C: спільні бібліотеки
  also a virtual package provided by libc6-udeb

• dep: libgcc-s1 (>= 3.5)

  Допоміжна бібліотека GCC

• dep: libstdc++6 (>= 5.2)

  Стандартна бібліотека C++ GNU, версії 3

• dep: r-api-4.0

  virtual package provided by r-base-core

• dep: r-base-core (>= 4.0.3-1)

  GNU R core of statistical computation and graphics system

• dep: r-cran-broom

  convert statistical analysis objects into tidy data frames with GNU R

• dep: r-cran-cpp11

  C++11 interface for GNU R's C interface

• dep: r-cran-dplyr

  GNU R grammar of data manipulation

• dep: r-cran-generics

  GNU R common S3 generics not provided by base R methods

• dep: r-cran-lattice

  GNU R package for 'Trellis' graphics

• dep: r-cran-rcpp

  GNU R package for Seamless R and C++ Integration

• dep: r-cran-rlang

  Functions for Base Types and Core R and 'Tidyverse' Features

• dep: r-cran-tidyr

  GNU R package to easily tidy data

• rec: r-cran-boot

  GNU R package for bootstrapping functions from Davison and Hinkley

• rec: r-cran-broom.mixed

  GNU R tidying methods for mixed models

• rec: r-cran-clipr

  Read and Write from the System Clipboard

• rec: r-cran-forcats

  GNU R package for working with categorical variables (factors)

• rec: r-cran-haven

  GNU R package to import/export SPSS, Stata and SAS files

• rec: r-cran-hms

  GNU R pretty time of day

• rec: r-cran-hsaur3

  Handbook of Statistical Analyses Using R (3rd Edition)

• rec: r-cran-jomo

  GNU R multilevel joint modelling multiple imputation

• rec: r-cran-lme4

  GNU R package for linear mixed effects model fitting

• rec: r-cran-lmtest

  GNU R package for diagnostic checking in linear models

• rec: r-cran-mass

  GNU R package of Venables and Ripley's MASS

• rec: r-cran-matrix

  GNU R package of classes for dense and sparse matrices

• rec: r-cran-metafor

  Meta-Analysis Package for R

• rec: r-cran-minqa

  GNU R package for quadratic optimisation without derivatives

• rec: r-cran-mitml

  GNU R tools for multiple imputation in multilevel modeling

• rec: r-cran-nloptr

  GNU R package for interface to NLopt

• rec: r-cran-nnet

  GNU R package for feed-forward neural networks

• rec: r-cran-numderiv

  GNU R package for accurate numerical derivatives

• rec: r-cran-ordinal

  GNU R regression models for ordinal data

• rec: r-cran-pan

  GNU R multiple imputation for multivariate panel or clustered data

• rec: r-cran-rcppeigen

  GNU R package for Eigen templated linear algebra

• rec: r-cran-readr

  GNU R package to read rectangular text data

• rec: r-cran-survival

  GNU R package for survival analysis

• rec: r-cran-testthat

  GNU R testsuite

• rec: r-cran-ucminf

  GNU R general-purpose unconstrained non-linear optimization

• sug: r-cran-knitr

  GNU R package for dynamic report generation using Literate Programming

• sug: r-cran-randomforest

  GNU R package implementing the random forest classificator

• sug: r-cran-rmarkdown

  convert R markdown documents into a variety of formats

• sug: r-cran-rpart

  GNU R package for recursive partitioning and regression trees

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