Package: LAM 0.8-1

LAM: Some Latent Variable Models

Includes some procedures for latent variable modeling with a particular focus on multilevel data. The 'LAM' package contains mean and covariance structure modelling for multivariate normally distributed data (mlnormal(); Longford, 1987; <doi:10.1093/biomet/74.4.817>), a general Metropolis-Hastings algorithm (amh(); Roberts & Rosenthal, 2001, <doi:10.1214/ss/1015346320>) and penalized maximum likelihood estimation (pmle(); Cole, Chu & Greenland, 2014; <doi:10.1093/aje/kwt245>).

Authors:Alexander Robitzsch [aut,cre]

LAM_0.8-1.tar.gz
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LAM_0.8-1.tgz(r-4.6-x86_64)LAM_0.8-1.tgz(r-4.6-arm64)LAM_0.8-1.tgz(r-4.5-x86_64)LAM_0.8-1.tgz(r-4.5-arm64)
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LAM_0.8-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
LAM/json (API)
NEWS

# Install 'LAM' in R:

install.packages('LAM', repos = c('https://alexanderrobitzsch.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/alexanderrobitzsch/lam/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

data.HT12 - Datasets from Heck and Thomas

On CRAN:

multilevel-models structural-equation-modeling openblas cpp

5.00 score 6 stars 1 packages 11 scripts 450 downloads 46 mentions 7 exports 12 dependencies

Last updated from:ff8d6aef2e. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	154
linux-devel-x86_64	OK	134
source / vignettes	OK	191
linux-release-arm64	OK	126
linux-release-x86_64	OK	125
macos-release-arm64	OK	116
macos-release-x86_64	OK	380
macos-oldrel-arm64	OK	86
macos-oldrel-x86_64	OK	185
windows-devel	OK	122
windows-release	OK	124
windows-oldrel	OK	134
wasm-release	OK	117

Exports:amh clpm_to_ctm loglike_mvnorm loglike_mvnorm_NA_pattern mlnormal pmle suff_stat_NA_pattern

Dependencies:admisc CDM lattice Matrix mvtnorm pbapply pbv polycor Rcpp RcppArmadillo sirt TAM

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Some Latent Variable Models	LAM-package LAM
Bayesian Model Estimation with Adaptive Metropolis Hastings Sampling ('amh') or Penalized Maximum Likelihood Estimation ('pmle')	amh coef.amh coef.pmle confint.amh confint.pmle logLik.amh logLik.pmle plot.amh plot.pmle pmle summary.amh summary.pmle vcov.amh vcov.pmle
Transformation of Path Coefficients of Cross-Lagged Panel Model	clpm_to_ctm
Datasets from Heck and Thomas (2015)	data.HT data.HT12
Log-Likelihood Value of a Multivariate Normal Distribution	loglike_mvnorm loglike_mvnorm_NA_pattern
(Restricted) Maximum Likelihood Estimation with Prior Distributions and Penalty Functions under Multivariate Normality	coef.mlnormal confint.mlnormal logLik.mlnormal mlnormal print.mlnormal summary.mlnormal vcov.mlnormal
Sufficient Statistics for Dataset with Missing Response Pattern	suff_stat_NA_pattern