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lvmcomp2 is an R package for fast estimation of latent variable models with high-dimensional latent variables and with constrained/penalized parameters.

For more information, please refer to: Zhang, S., & Chen, Y. (2022). Computation for Latent Variable Model Estimation: A Unified Stochastic Proximal Framework.

Why lvmcomp2?

• Fast. By using state-of-the-art proximal quasi-Newton SA algorithms, lvmcomp2 is much quicker than commonly implemented numerical integration methods or the Stochastic EM algorithm.
• General. Include a general class of algorithms capable of handling many latent variable models.
• Written concisely in a combination of R and C++.

Install the lvmcomp2 package from GitHub

## install required packages
required_packages <- c("remotes", "Rcpp", "RcppArmadillo")
new_packages <- required_packages[!(required_packages %in% installed.packages()[,"Package"])]
if(length(new_packages)) install.packages(new_packages)

remotes::install_github("slzhang-fd/lvmcomp2")

Usage

Check an example in (More will be added soon)

• Example 1