1 # Buildsheet autogenerated by ravenadm tool -- Do not edit.
7 SDESC[standard]= Latent Variable Models
8 HOMEPAGE= https://kkholst.github.io/lava/
9 CONTACT= CRAN_Automaton[cran@ironwolf.systems]
12 SITES[main]= CRAN/src/contrib
13 https://loki.dragonflybsd.org/cranfiles/
14 DISTFILE[1]= lava_1.7.3.tar.gz:main
17 SPKGS[standard]= single
19 OPTIONS_AVAILABLE= none
20 OPTIONS_STANDARD= none
22 BUILDRUN_DEPENDS= R-future.apply:single:standard
23 R-numDeriv:single:standard
24 R-progressr:single:standard
25 R-SQUAREM:single:standard
33 INSTALL_REQ_TOOLCHAIN= yes
35 [FILE:809:descriptions/desc.single]
36 lava: Latent Variable Models
38 A general implementation of Structural Equation Models with latent
39 variables (MLE, 2SLS, and composite likelihood estimators) with both
40 continuous, censored, and ordinal outcomes (Holst and Budtz-Joergensen
41 (2013) <<a href="https://doi.org/10.1007%2Fs00180-012-0344-y"
42 target="_top">doi:10.1007/s00180-012-0344-y</a>>). Mixture latent
43 variable models and non-linear latent variable models (Holst and
44 Budtz-Joergensen (2020) <<a
45 href="https://doi.org/10.1093%2Fbiostatistics%2Fkxy082"
46 target="_top">doi:10.1093/biostatistics/kxy082</a>>). The package also
47 provides methods for graph exploration (d-separation, back-door criterion),
48 simulation of general non-linear latent variable models, and estimation of
49 influence functions for a broad range of statistical models.
53 4e087df1350b05c3d0403597a1ad97f4b0e183047d5d8636a62143f26bd86a08 1182397 CRAN/lava_1.7.3.tar.gz