Fast Estimation for Latent Variable Models using the Unified Stochastic Proximal (USP) Algorithms
Provides stochastic approximation algorithms for latent variable models with a high-dimensional latent space and with constraints/penalized parameters. So far, we provide functions for confirmatory item factor analysis based on the multidimensional two parameter logistic (M2PL) model. The computation is facilitated by multiprocessing 'OpenMP' API.
For more information, please refer to: Zhang, S., & Chen, Y. (2022). Computation for Latent Variable Model Estimation: A Unified Stochastic Proximal Framework.