c(person("Klaus K.", "Holst", email="klaus@holst.it", role=c("aut", "cre")),
		   person("Brice", "Ozenne", role = "ctb"),
		   person("Thomas", "Gerds", role = "ctb"))
Klaus K. Holst [aut, cre],
  Brice Ozenne [ctb],
  Thomas Gerds [ctb]
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>).
	Mixture latent variable models and non-linear latent variable models
	(Holst and Budtz-Joergensen (2020) <doi:10.1093/biostatistics/kxy082>).
	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.
future.apply, grDevices, graphics, methods, numDeriv,
progressr, stats, survival, SQUAREM, utils
KernSmooth, Matrix, Rgraphviz, data.table, ellipse, fields,
geepack, graph, knitr, bookdown, rmarkdown, igraph (>= 0.6),
lavaSearch2, lme4, mets (>= 1.1), nlme, optimx, polycor,
quantreg, rgl, R.rsp (>= 0.40), targeted (>= 0.2), testthat (>=
0.11), visNetwork, zoo