{ "_id": "6ada306d343c88418cb71e73", "Package": "spifa", "Type": "Package", "Title": "Bayesian Spatial Item Factor Analysis", "Version": "0.1.0", "Encoding": "UTF-8", "Authors@R": "c(\nperson(c(\"Erick\", \"A.\"), \"Chacón-Montalván\", , \"erick.chaconmontalvan@wur.nl\",\nrole = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0001-8068-1034\")),\nperson(\"Emanuele\", \"Giorgi\", role = \"ctb\"),\nperson(\"Benjamin M.\", \"Taylor\", role = \"ctb\"))", "Description": "Fits spatial item factor analysis models for binary\nresponses, following Chacón-Montalván, E. A., Parry, L.,\nGiorgi, E., Torres, P., Orellana, J. D. Y., Moraga, P., and\nTaylor, B. M. (2025) , using full\nBayesian inference via adaptive Metropolis-Hastings within\nGibbs sampling and auxiliary variables with a probit link\nfunction. The latent factors are modelled as the sum of a\npredictor effect, a multivariate Gaussian process capturing\nspatial dependence, and a multivariate non-spatial term,\nallowing users to fit and predict spatially-referenced\nconstructs such as food insecurity or socioeconomic indices.\nStandard exploratory and confirmatory item factor analysis are\nsupported as particular cases, simply by dropping the spatial\nstructure.", "License": "GPL-3", "URL": "https://github.com/ErickChacon/spifa,\nhttps://ErickChacon.github.io/spifa/", "BugReports": "https://github.com/ErickChacon/spifa/issues", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Config/roxygen2/version": "8.0.0", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-10-22 15:42:20 UTC", "User": "root" }, "Author": "Erick A. Chacón-Montalván [aut, cre] (ORCID:\n), Emanuele Giorgi\n[ctb], Benjamin M. Taylor [ctb]", "Maintainer": "Erick A. 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