spfa_example

<p>An R object containing an example output from fitting an spfa model using the following code:
# RT &lt;- spfa::simdata[,1:8]
# spfa_example &lt;- spfa(data = RT, dimension = rep(0, ncol(RT)), discrete = rep(FALSE, ncol(RT)))</p>

data

Estimation, scoring, and plotting functions for the semi-parametric factor model proposed by Liu & Wang (2022) <doi:10.1007/s11336-021-09832-8> and Liu & Wang (2023) <arXiv:2303.10079>. 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.

spfa_example: spfa_example

Description

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