Пакунок: r-cran-lava (1.6.4-1)

[ Source: r-cran-lava  ]

GNU R latent variable models

A general implementation of Structural Equation Models with latent variables (MLE, 2SLS, and composite likelihood estimators) with both continuous, censored, and ordinal outcomes (Holst and Budtz-Joergensen (2013) <doi:10.1007/s00180-012-0344-y>). The package also provides methods for graph exploration (d-separation, back-door criterion), simulation of general non-linear latent variable models, and estimation of influence functions for a broad range of statistical models.

Інші пакунки пов'язані з r-cran-lava

• dep: r-api-3.5

  virtual package provided by r-base-core

• dep: r-base-core (>= 3.5.1-2)

  GNU R core of statistical computation and graphics system

• dep: r-cran-numderiv

  GNU R package for accurate numerical derivatives

• dep: r-cran-squarem

  Squared Extrapolation Methods for Accelerating EM-Like Monotone Algorithms

• dep: r-cran-survival

  GNU R package for survival analysis

• rec: r-cran-testthat (>= 0.11)

  GNU R testsuite

• sug: r-bioc-graph

  handle graph data structures for BioConductor

• sug: r-cran-data.table

  GNU R extension of Data.frame

• sug: r-cran-ellipse

  GNU R functions for drawing ellipses and ellipse-like confidence regions

• sug: r-cran-fields

  GNU R tools for spatial data

• sug: r-cran-foreach

  GNU R foreach looping support

• sug: r-cran-geepack

  Generalized Estimating Equation Package for R

• sug: r-cran-igraph (>= 0.6)

  GNU R network analysis and visualization

• sug: r-cran-kernsmooth

  GNU R package for kernel smoothing and density estimation

• sug: r-cran-lme4

  GNU R package for linear mixed effects model fitting

• sug: r-cran-matrix

  GNU R package of classes for dense and sparse matrices

• sug: r-cran-nlme

  GNU R package for (non-)linear mixed effects models

• sug: r-cran-quantreg

  GNU R package for quantile regression

• sug: r-cran-rgl

  GNU R package for three-dimensional visualisation using OpenGL

• sug: r-cran-zoo

  GNU R package for totally ordered indexed observations

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