lava (1.6.7)

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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) ). Mixture latent variable models and non-linear latent variable models (Holst and Budtz-Joergensen (2019) ). 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, nlme, quantreg, rgl, zoo, polycor, data.table, gof, foreach, testthat, optimx, mets, lava.tobit, visNetwork
Reverse depends: gof, lava.tobit, lavaSearch2, mets, targeted
Reverse suggests: gof, pec, prodlim, riskRegression, soil.spec

Released 3 months ago.

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