{ "_id": "6a1f306ab401979e73427815", "Package": "panelPomp", "Type": "Package", "Title": "Inference for Panel Partially Observed Markov Processes", "Version": "1.7.0.0", "Authors@R": "c(person(given=\"Carles\",family=\"Breto\",role=\"aut\",email=\"carles.breto@uv.es\",comment=c(ORCID=\"0000-0003-4695-4902\")),\nperson(given=c(\"Edward\",\"L.\"),family=\"Ionides\",role=\"aut\",comment=c(ORCID=\"0000-0002-4190-0174\")),\nperson(given=c(\"Aaron\",\"A.\"),family=\"King\",role=\"aut\",comment=c(ORCID=\"0000-0001-6159-3207\")),\nperson(given=\"Jesse\",family=\"Wheeler\",role=c(\"aut\",\"cre\"),email=\"jeswheel@umich.edu\",comment=c(ORCID=\"0000-0003-3941-3884\")),\nperson(given=\"Aaron\",family=\"Abkemeier\",role=c(\"ctb\"),email=\"aaronabk@umich.edu\"))", "Description": "Data analysis based on panel partially-observed Markov\nprocess (PanelPOMP) models. To implement such models, simulate\nthem and fit them to panel data, 'panelPomp' extends some of\nthe facilities provided for time series data by the 'pomp'\npackage. Implemented methods include filtering (panel particle\nfiltering) and maximum likelihood estimation (Panel Iterated\nFiltering) as proposed in Breto, Ionides and King (2020) \"Panel\nData Analysis via Mechanistic Models\"\n.", "License": "GPL-3", "RoxygenNote": "7.3.2", "Encoding": "UTF-8", "Collate": "'panelPomp-package.R' 'aaa.R' 'contacts.R' 'generics.R'\n'get_col_row.R' 'panel_loglik.R' 'panel_logmeanexp.R'\n'panelPomp.R' 'panelPomp_methods.R' 'params.R' 'pfilter.R'\n'pfilter_methods.R' 'mif2.R' 'mif2_methods.R' 'panelGompertz.R'\n'panelGompertzLikelihood.R' 'panelMeasles.R'\n'panelRandomWalk.R' 'panel_designs.R' 'plot.R' 'simulate.R'\n'twentycities.R' 'uk_measles.R'", "Roxygen": "list(markdown = TRUE)", "VignetteBuilder": "knitr", "LazyData": "true", "Repository": "https://jeswheel.r-universe.dev", "Date/Publication": "2025-05-19 19:46:55 UTC", "RemoteUrl": "https://github.com/jeswheel/panelpomp", "RemoteRef": "HEAD", "RemoteSha": "18facbbfcb336054f6f5aed974ffea4db66fe201", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-15 08:45:57 UTC", "User": "root" }, "Author": "Carles Breto [aut] (ORCID: ),\nEdward L. 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