{ "_id": "6a1f1c67b401979e7341f86c", "Package": "spatemR", "Type": "Package", "Title": "Generalized Spatial Autoregresive Models for Mean and Variance", "Version": "1.3.0", "Authors@R": "c(person(\"Nelson Alirio\", \"Cruz Gutierrez\", \nrole = c(\"aut\", \"cre\",\"cph\"), email = \"nelson-alirio.cruz@uib.es\"),\nperson(\"Oscar Orlando\", \"Melo\", role = \"aut\",\nemail=\"oomelom@unal.edu.co\"),\nperson(\"Jurgen\", \"Toloza-Delgado\", role = \"aut\",\nemail=\"jdtolozad@unal.edu.co\"))", "Description": "Modeling spatial dependencies in dependent variables,\nextending traditional spatial regression approaches. It allows\nfor the joint modeling of both the mean and the variance of the\ndependent variable, incorporating semiparametric effects in\nboth models. Based on generalized additive models (GAM), the\npackage enables the inclusion of non-parametric terms while\nmaintaining the classical theoretical framework of spatial\nregression. Additionally, it implements the Generalized Spatial\nAutoregression (GSAR) model, which extends classical methods\nlike logistic Spatial Autoregresive Models (SAR), probit\nSpatial Autoregresive Models (SAR), and Poisson Spatial\nAutoregresive Models (SAR), offering greater flexibility in\nmodeling spatial dependencies and significantly improving\ncomputational efficiency and the statistical properties of the\nestimators. Related work includes: a) J.D. Toloza-Delgado, Melo\nO.O., Cruz N.A. (2024). \"Joint spatial modeling of mean and\nnon-homogeneous variance combining semiparametric SAR and\nGAMLSS models for hedonic prices\".\n. b) Cruz, N. A.,\nToloza-Delgado, J. D., Melo, O. O. (2024). \"Generalized spatial\nautoregressive model\". .", "License": "GPL (>= 3)", "Encoding": "UTF-8", "Config/testthat/edition": "3", "RoxygenNote": "7.3.3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-16 08:58:25 UTC", "User": "root" }, "Author": "Nelson Alirio Cruz Gutierrez [aut, cre, cph], Oscar Orlando\nMelo [aut], Jurgen Toloza-Delgado [aut]", "Maintainer": "Nelson Alirio Cruz Gutierrez ", "Config/pak/sysreqs": "libabsl-dev cmake libgdal-dev gdal-bin libgeos-dev\nlibicu-dev libssl-dev libproj-dev libsqlite3-dev\nlibudunits2-dev", "Repository": "https://cruzalirio.r-universe.dev", "Date/Publication": "2026-04-16 16:23:38 UTC", "RemoteUrl": "https://github.com/cruzalirio/spatemr", "RemoteRef": "HEAD", "RemoteSha": "f63261fa6d19b6dd6ae6b641a00dbc2f30f3e604", "MD5sum": "04bca9a012e0666437ddd5dd5bda3687", "_user": "cruzalirio", "_type": "src", "_file": "spatemR_1.3.0.tar.gz", "_fileid": "5235ab9c84b1f023cf0fe4dab2ac1cd820d196d8d51024fef3dd79d71b7cba30", "_filesize": 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