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lamle  

Maximum Likelihood Estimation of Latent Variable Models
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]
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 01 May. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited lamle R package
View lamle citation profile
Other R packages that lamle depends, 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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