spfa

Semi-Parametric Factor Analysis

CRAN Package

Estimation, scoring, and plotting functions for the semi-parametric factor model proposed by Liu & Wang (2022) and Liu & Wang (2023) . Both the conditional densities of observed responses given the latent factors and the joint density of latent factors are estimated non-parametrically. Functional parameters are approximated by smoothing splines, whose coefficients are estimated by penalized maximum likelihood using an expectation-maximization (EM) algorithm. E- and M-steps can be parallelized on multi-thread computing platforms that support 'OpenMP'. Both continuous and unordered categorical response variables are supported.


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