{ "_id": "6a48a8f7e06c18f0a6545a5d", "Package": "tsfgrnn", "Type": "Package", "Title": "Time Series Forecasting Using GRNN", "Version": "1.0.5", "Authors@R": "c(\nperson(\"Maria Pilar\", \"Frias-Bustamante\", role = c(\"aut\"), email = \"mpfrias@ujaen.es\"),\nperson(\"Ana Maria\", \"Martinez-Rodriguez\", role = c(\"aut\"), email = \"ammartin@ujaen.es\"),\nperson(\"Antonio\", \"Conde-Sanchez\", role = c(\"aut\"), email = \"aconde@ujaen.es\"),\nperson(\"Francisco\", \"Martinez\", role = c(\"aut\", \"cre\"), email = \"fmartin@ujaen.es\"))", "Maintainer": "Francisco Martinez ", "Description": "A general regression neural network (GRNN) is a variant of\na Radial Basis Function Network characterized by a fast\nsingle-pass learning. 'tsfgrnn' allows you to forecast time\nseries using a GRNN model Francisco Martinez et al. (2019)\n and Francisco Martinez et\nal. (2022) . When the\nforecasting horizon is higher than 1, two multi-step ahead\nforecasting strategies can be used. The model built is\nautoregressive, that is, it is only based on the observations\nof the time series. You can consult and plot how the prediction\nwas done. It is also possible to assess the forecasting\naccuracy of the model using rolling origin evaluation.", "License": "GPL-2", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.2.3", "VignetteBuilder": "knitr", "URL": "https://github.com/franciscomartinezdelrio/tsfgrnn", "BugReports": "https://github.com/franciscomartinezdelrio/tsfgrnn", "Config/testthat/edition": "3", "Repository": "https://franciscomartinezdelrio.r-universe.dev", "Date/Publication": "2024-02-15 08:35:10 UTC", "RemoteUrl": "https://github.com/franciscomartinezdelrio/tsfgrnn", "RemoteRef": "HEAD", "RemoteSha": "3dea6b4fa42ef2ffcf29a92bd8c21541dc3b7d41", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-07-04 06:03:07 UTC", "User": "root" }, "Author": "Maria Pilar Frias-Bustamante [aut],\nAna Maria Martinez-Rodriguez [aut],\nAntonio Conde-Sanchez [aut],\nFrancisco Martinez [aut, cre]", "_user": "franciscomartinezdelrio", "_type": "src", "_file": "tsfgrnn_1.0.5.tar.gz", "_fileid": 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