{ "_id": "6a1f0443b401979e7341b741", "Package": "spStack", "Type": "Package", "Version": "1.1.3.99", "Title": "Bayesian Geostatistics Using Predictive Stacking", "Authors@R": "c(\nperson(\"Soumyakanti\", \"Pan\", role = c(\"aut\", \"cre\"),\nemail = \"span18@ucla.edu\", comment = c(ORCID = \"0009-0005-9889-7112\")),\nperson(\"Sudipto\", \"Banerjee\", role = \"aut\", email = \"sudipto@ucla.edu\"))", "Description": "Fits Bayesian hierarchical spatial and spatial-temporal\nprocess models for point-referenced Gaussian, Poisson,\nbinomial, and binary data using stacking of predictive\ndensities. It involves sampling from analytically available\nposterior distributions conditional upon candidate values of\nthe spatial process parameters and, subsequently assimilate\ninference from these individual posterior distributions using\nBayesian predictive stacking. Our algorithm is highly\nparallelizable and hence, much faster than traditional Markov\nchain Monte Carlo algorithms while delivering competitive\npredictive performance. See Zhang, Tang, and Banerjee (2025)\n, and, Pan, Zhang, Bradley,\nand Banerjee (2025) for details.", "NeedsCompilation": "yes", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "Config/testthat/edition": "3", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "URL": "https://span-18.github.io/spStack-dev/", "BugReports": "https://github.com/SPan-18/spStack-dev/issues", "Language": "en-US", "Config/pak/sysreqs": "cmake libgmp3-dev make pkg-config libclang-dev", "Repository": "https://span-18.r-universe.dev", "Date/Publication": "2026-05-18 07:31:59 UTC", "RemoteUrl": "https://github.com/span-18/spstack-dev", "RemoteRef": "HEAD", "RemoteSha": "9f8d20e4848ef665e7bbaa24c01b5f34b46f08fb", "Packaged": { "Date": "2026-05-18 07:46:51 UTC", "User": "root" }, "Author": "Soumyakanti Pan [aut, cre] (ORCID:\n),\nSudipto Banerjee [aut]", "Maintainer": "Soumyakanti Pan ", "MD5sum": "6e7ee97bfdc879eb614f57a1b529ff35", "_user": "span-18", "_type": 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