{ "_id": "6acd72f3a14063b82c3aba87", "Package": "Dogoftest", "Title": "Distributed Online Goodness-of-Fit Tests for Distributed\nDatasets", "Version": "0.4.2", "Authors@R": "c(person(\"Guangbao\", \"Guo\",role = c(\"aut\", \"cre\"),\nemail = \"ggb11111111@163.com\",\ncomment = c(ORCID = \"0000-0002-4115-6218\")),\nperson(\"Di\", \"Chang\", role=\"aut\"))", "Description": "Distributed Online Goodness-of-Fit Test can process the\ndistributed datasets. 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"2026-42", "n": 1 } ], "_tags": [ { "name": "0.4.2", "date": "2026-10-12" } ], "_stars": 0, "_contributors": [ { "user": "guangbaog", "count": 4, "uuid": 141387511 } ], "_userbio": { "uuid": 141387511, "type": "user", "name": "Guangbao Guo", "followers": 3 }, "_downloads": { "count": 250, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/Dogoftest" }, "_searchresults": 0, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/Dogoftest.html", "extra/manual.pdf", "LICENSE" ], "_realowner": "guangbaog", "_cranurl": false, "_releases": [ { "version": "0.1", "date": "2025-02-18" }, { "version": "0.2", "date": "2025-06-24" }, { "version": "0.3", "date": "2025-08-01" }, { "version": "0.4.2", "date": "2026-10-12" } ], "_exports": [ "AD2gof", "ADgof", "CVM2gof", "CVMgof", "DAD", "DAD2", "DCVM", "DCVM2", "DKS", "DKS2", "DPECVM", "DPECVM2", "KS2gof", "KSgof", "Kuiper2gof", "PE2AD", "PE2CVM", "PE2KS", "PECVM", "PEKS", "qCvMgof", "run_custom_tests", "run_FDP_sim", "simpleCvMgof", "Wgof" ], "_datasets": [ { "name": "BSdata", "title": "Data set", "object": "BSdata", "class": [ "list" ], "fields": [], "table": false, "tojson": true }, { "name": "goats", "title": "Zoometric measurements of goats", "object": "goats", "class": [ "data.frame" ], "fields": [ "body.weight", "body.length", "trunk.length", "withers.height", "thoracic.perimeter", "hip.length", "ear.length" ], "rows": 52, "table": true, "tojson": true }, { "name": "snow", "title": "Snow Dataset", "object": "Snow", "class": [ "numeric" ], "fields": [], "table": false, "tojson": true }, { "name": "strength", "title": "Compressive strength of maize seeds", "object": "strength", "class": [ "data.frame" ], "fields": [ "strain", "cstrength" ], "rows": 90, "table": true, "tojson": true }, { "name": "WhiteWine", "title": "White Wine Quality Data", "object": "WhiteWine", "class": [ "data.frame" ], "fields": [ "quality", "fixed.acidity", "volatile.acidity", "citric.acid", "residual.sugar", "chlorides", "free.sulfur.dioxide", "total.sulfur.dioxide", "density", "pH", "sulphates", "alcohol" ], "rows": 4898, "table": true, "tojson": true } ], "_help": [ { "page": "AD2gof", "title": "Two-Sample Anderson-Darling Permutation Test", "topics": [ "AD2gof" ] }, { "page": "ADgof", "title": "Anderson-Darling Test for Normality", "topics": [ "ADgof" ] }, { "page": "BSdata", "title": "Data set", "topics": [ "BSdata" ] }, { "page": "CVM2gof", "title": "Two-Sample Cramér-von Mises Permutation Test", "topics": [ "CVM2gof" ] }, { "page": "CVMgof", "title": "One-Sample Cramér–von Mises Test for Normality", "topics": [ "CVMgof" ] }, { "page": "DAD", "title": "DAD This function implements a resampling-based AD goodness-of-fit test. It draws K bootstrap subsamples, performs AD goodness-of-fit test on each subsample, returns the average AD statistic and the minimum p-value across all K subsamples.", "topics": [ "DAD" ] }, { "page": "DAD2", "title": "Distributed Two-Sample Anderson-Darling Test via Fisher Combination", "topics": [ "DAD2" ] }, { "page": "DCVM", "title": "DCVM This function implements a resampling-based CVM goodness-of-fit test. It draws K bootstrap subsamples, performs CVM goodness-of-fit test on each subsample, returns the average CVM statistic and the minimum p-value across all K subsamples.", "topics": [ "DCVM" ] }, { "page": "DCVM2", "title": "Distributed Two-Sample Cramér-von Mises Test via Fisher Combination", "topics": [ "DCVM2" ] }, { "page": "DKS", "title": "DKS This function implements a resampling-based KS test. It draws K bootstrap subsamples, performs KS goodness-of-fit test on each subsample, returns the average KS statistic and the minimum p-value across all K subsamples.", "topics": [ "DKS" ] }, { "page": "DKS2", "title": "Distributed Two-Sample KS Test via Fisher Combination", "topics": [ "DKS2" ] }, { "page": "DPECVM", "title": "DPECVM Performs the divided PECVM goodness-of-fit test. The original sample is split into K bootstrap subsamples, PECVM test is applied on each subsample. The final test statistic is the average of subsample statistics, and the p-value is taken as the minimum of subsample p-values.", "topics": [ "DPECVM" ] }, { "page": "DPECVM2", "title": "Distributed Power-Enhanced Two-Sample Cramer-von Mises Test", "topics": [ "DPECVM2" ] }, { "page": "goats", "title": "Zoometric measurements of goats", "topics": [ "goats" ] }, { "page": "KS2gof", "title": "Two-Sample Kolmogorov-Smirnov Test with Bootstrap/Permutation", "topics": [ "KS2gof" ] }, { "page": "KSgof", "title": "One-sample Kolmogorov-Smirnov goodness-of-fit test", "topics": [ "KSgof" ] }, { "page": "Kuiper2gof", "title": "Two-Sample Kuiper Test with Bootstrap", "topics": [ "Kuiper2gof" ] }, { "page": "PE2AD", "title": "Power-Enhanced Two-Sample Anderson-Darling Test (PE2AD)", "topics": [ "PE2AD" ] }, { "page": "PE2CVM", "title": "Power-Enhanced Two-Sample Cramer-von Mises Test (PE2CVM)", "topics": [ "PE2CVM" ] }, { "page": "PE2KS", "title": "Power-Enhanced Two-Sample Kolmogorov–Smirnov Test (PE2KS)", "topics": [ "PE2KS" ] }, { "page": "PECVM", "title": "Power-Enhanced Cramer-von Mises Goodness-of-Fit Test", "topics": [ "PECVM" ] }, { "page": "PEKS", "title": "Power-Enhanced Kolmogorov–Smirnov Goodness-of-Fit Test", "topics": [ "PEKS" ] }, { "page": "qCvMgof", "title": "Calculate the Quantile of the Cramer-von Mises Goodness-of-Fit Statistic", "topics": [ "qCvMgof" ] }, { "page": "run_custom_tests", "title": "Run four goodness-of-fit tests for normality", "topics": [ "run_custom_tests" ] }, { "page": "run_FDP_sim", "title": "Compute False Discovery Proportion (FDP) via Monte Carlo simulation for DKS, DCVM, DAD and DPECVM tests.", "topics": [ "run_FDP_sim" ] }, { "page": "simpleCvMgof", "title": "Perform a Simple Cramer-von Mises Goodness-of-Fit Test", "topics": [ "simpleCvMgof" ] }, { "page": "snow", "title": "Snow Dataset", "topics": [ "Snow", "snow" ] }, { "page": "strength", "title": "Compressive strength of maize seeds", "topics": [ "strength" ] }, { "page": "Wgof", "title": "Watson goodness-of-fit test Performs the Watson test for goodness-of-fit to a specified distribution.", "topics": [ "Wgof" ] }, { "page": "WhiteWine", "title": "White Wine Quality Data", "topics": [ "WhiteWine" ] } ], "_rundeps": [], "_score": 1, "_indexed": true, "_nocasepkg": "dogoftest", "_universes": [ "guangbaog" ], "_previous": "0.3", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.4.2", "date": "2026-10-12T23:24:25.000Z", "distro": "resolute", "commit": "e9a3e265a0323846a3de30656afe3eb55aeca6f0", "fileid": "https://r2.ropensci.org/48c7531b54477cca2b739b628687518ee4d658b6e5d48d77a956e8c83d080fa1", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/guangbaog/actions/runs/38321423253" }, { "r": "4.6.1", "os": "linux", "version": "0.4.2", "date": "2026-10-12T23:24:25.000Z", "distro": "resolute", "commit": "e9a3e265a0323846a3de30656afe3eb55aeca6f0", "fileid": 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