{ "_id": "6ad740994b18b900899997f7", "Package": "Dogoftest", "Title": "Distributed Online Goodness-of-Fit Tests for Distributed\nDatasets", "Version": "0.4.3", "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. The philosophy of the package is\ndescribed in Guo G.(2024) .", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "RoxygenNote": "7.3.3", "LazyData": "true", "Config/testthat/edition": "3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-20 10:18:49 UTC", "User": "root" }, "Author": "Guangbao Guo [aut, cre] (ORCID:\n), Di Chang [aut]", "Maintainer": "Guangbao Guo ", "Repository": "https://guangbaog.r-universe.dev", "Date/Publication": "2026-10-19 23:50:02 UTC", "RemoteUrl": "https://github.com/cran/Dogoftest", "RemoteRef": "HEAD", "RemoteSha": "338923687b87abed076b67d7edb79bfe54fc4836", "_user": "guangbaog", "_type": "src", "_file": "Dogoftest_0.4.3.tar.gz", "_fileid": "https://r2.ropensci.org/d37fa6f51e90b973c5ccbeedeea02ab4f97de7c224d59eeab2f8f2740dd124ab", "_filesize": 519778, "_sha256": "d37fa6f51e90b973c5ccbeedeea02ab4f97de7c224d59eeab2f8f2740dd124ab", "_expires": "2027-01-28T10:21:12.000Z", "_created": "2026-10-20T10:18:49.000Z", "_published": 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"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": "simulate_power", "title": "Monte Carlo Power Simulation for Goodness-of-Fit Tests", "topics": [ "simulate_power" ] }, { "page": "snow", "title": "Snow Dataset", "topics": [ "Snow", 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