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lamle
View on CRAN: Click
here
Download and install lamle package within the R console
Install from CRAN:
install.packages("lamle")
Install from Github:
library("remotes")
install_github("cran/lamle") Install by package version:
library("remotes")
install_version("lamle", "0.3.1") Attach the package and use:
library("lamle")
Maintained by
Björn Andersson
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-08-25
Latest Update: 2023-08-25
Description:
Approximate marginal maximum likelihood estimation of multidimensional
latent variable models via adaptive quadrature or Laplace approximations to the
integrals in the likelihood function, as presented for confirmatory factor
analysis models in Jin, S., Noh, M., and Lee, Y. (2018)
, for item response theory models in
Andersson, B., and Xin, T. (2021) , and for
generalized linear latent variable models in Andersson, B., Jin, S., and
Zhang, M. (2023) . Models implemented include
the generalized partial credit model, the graded response model, and generalized
linear latent variable models for Poisson, negative-binomial and normal
distributions. Supports a combination of binary, ordinal, count and continuous
observed variables and multiple group models.
How to cite:
Björn Andersson (2023). lamle: Maximum Likelihood Estimation of Latent Variable Models. R package version 0.3.1, https://cran.r-project.org/web/packages/lamle. Accessed 26 Oct. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for lamle
Functions, R codes and Examples using
the lamle R package
Some associated functions: DGP . lamle-package . lamle.compute . lamle.fit . lamle . lamle.plot . lamle.predict . lamle.sim . lamleout-class .
Some associated R codes: RcppExports.R . Full lamle package functions and examples
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