{ "_id": "6ab6472599f7aa8c6aa2d181", "Package": "psvr", "Title": "Percentage-Error Support Vector Regression", "Version": "0.1.0", "Authors@R": "person(\"Pablo\", \"Benavides-Herrera\", email = \"pbenavides@iteso.mx\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-4926-4763\"))", "Description": "Implements four support vector regression (SVR) models\nderived from a unified mathematical framework for\npercentage-error loss functions: epsilon-SVR minimizing the\nmean absolute percentage error (MAPE), its symmetric kernel\nextension, least-squares SVR (LS-SVR) minimizing the root mean\nsquare percentage error (RMSPE), and its symmetric counterpart.\nAll models require strictly positive targets. The epsilon-SVR\nmodels are solved via a built-in sequential minimal\noptimization (SMO) algorithm (with 'osqp' available as an\noptional alternative backend) and the LS-SVR models via a\nlinear system (base R). See Benavides-Herrera et al. (2026)\n for the mathematical derivations.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "Config/testthat/edition": "3", "VignetteBuilder": "knitr", "URL": "https://pbenavidesh.github.io/psvr/", "Config/Needs/website": "rmarkdown, tsibbledata, tsibble, lubridate,\nggplot2, kableExtra, kernlab, scales, tidyr, tidyverse,\ntidymodels, modeldata, future, ranger, xgboost, ggrepel,\nsessioninfo, modeltime, timetk, randomForest, readxl, xfun,\ne1071, quantreg, lars, patchwork, here", "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev", "Repository": "https://pbenavidesh.r-universe.dev", "Date/Publication": "2026-09-14 19:54:03 UTC", "RemoteUrl": "https://github.com/pbenavidesh/psvr", "RemoteRef": "HEAD", "RemoteSha": "27c25944942c9ef3e2f887fbe840c45348d27fdb", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-09-25 09:55:10 UTC", "User": "root" }, "Author": "Pablo Benavides-Herrera [aut, cre] (ORCID:\n)", 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