lava (1.6)

0 users

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) ). 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.

Maintainer: Klaus K. Holst
Author(s): Klaus K. Holst [aut, cre], Brice Ozenne [ctb], Thomas Gerds [ctb]

License: GPL-3

Uses: numDeriv, SQUAREM, survival, KernSmooth, Matrix, ellipse, fields, geepack, graph, igraph, lme4, quantreg, rgl, zoo, data.table, ascii, gof, foreach, testthat, optimx, mets, lava.tobit, visNetwork
Reverse depends: lava.tobit, lavaSearch2, mets
Reverse suggests: gof, pec, prodlim, riskRegression, soil.spec

Released 2 months ago.

25 previous versions



  (0 votes)


  (0 votes)

Log in to vote.


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

Related packages: AnalyzeFMRI, FactoMineR, GPArotation, MBESS, MCMCpack, MLDS, PTAk, RaschSampler, SensoMineR, VGAM, ade4, betareg, ca, cocorresp, e1071, eRm, eba, ecodist, elasticnet, fastICA(20 best matches, based on common tags.)

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

Visit lava on R Graphical Manual.