Routines for log-linear models of incomplete contingency tables,
including some latent class models, via EM and Fisher scoring
approaches. Allows bootstrapping. See Espeland and Hui (1987)
<doi:10.2307/2531553> for general approach.

Generalized Linear Latent Variable Models
Jenni Niku, Wesley Brooks, Riki Herliansyah, Francis K.C. Hui, Sara Taskinen, David I. Warton
Generalized linear latent variable model (gllvm) for analyzing multivariate data.
Estimation is performed using either Laplace approximation or variational approximation method implemented via TMB (Kristensen et al., (2016), <doi:10.18637/jss.v070.i05>).
Details for gllvm, see Hui et al. (2015) <doi:10.1111/2041-210X.12236>
and (2017) <doi:10.1080/10618600.2016.1164708> and Niku et al. (2017)
<doi:10.1007/s13253-017-0304-7>.
Rcpp (>= 0.12.11), MASS, Matrix, mvtnorm, statmod, fishMod

Analysis of multivariate data using generalized linear latent variable models (gllvm).
Estimation is performed using either Laplace approximation method or variational approximation method implemented via TMB (Kristensen et al., (2016), <doi:10.18637/jss.v070.i05>).
Details for gllvm, see Hui et al. (2015) <doi:10.1111/2041-210X.12236>
and (2017) <doi:10.1080/10618600.2016.1164708> and Niku et al. (2017)
<doi:10.1007/s13253-017-0304-7>.

MASS, Matrix, mvtnorm, statmod, fishMod, mgcv

Analysis of multivariate data using generalized linear latent variable models (gllvm).
Estimation is performed using either Laplace approximation method or variational approximation method implemented via TMB (Kristensen et al., (2016), <doi:10.18637/jss.v070.i05>).
For details see Niku et al. (2019) <doi:10.1371/journal.pone.0216129>.
knitr, rmarkdown, testthat, gclus, corrplot, lattice

Analysis of multivariate data using generalized linear latent variable models (gllvm).
Estimation is performed using either Laplace approximation method or variational approximation method implemented via TMB (Kristensen et al., (2016), <doi:10.18637/jss.v070.i05>).
For details see Niku et al. (2019a) <doi:10.1371/journal.pone.0216129> and Niku et al. (2019b) <doi:10.1111/2041-210X.13303>.