{ "_id": "6a60745314e95619b75d9d64", "Package": "steinsampling", "Title": "Kernel Stein Discrepancy Goodness-of-Fit and Stein Sampling\nTools", "Version": "0.1.0", "Date": "2026-07-11", "Authors@R": "c(\nperson(\"Junhao\", \"Gao\",\nemail = \"jug049@ucsd.edu\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Ery\", \"Arias-Castro\",\nemail = \"eariascastro@ucsd.edu\",\nrole = \"aut\")\n)", "Maintainer": "Junhao Gao ", "Description": "Provides Stein-discrepancy goodness-of-fit tests and\nStein-method-based sampling tools. The tests include kernel\nStein discrepancy U- and V-statistics following Liu et al.\n(2016) and Chwialkowski et al.\n(2016) , plus the finite set\nStein discrepancy test of Jitkrittum et al. (2017)\n. The sampling tools include\nStein thinning, Stein Points, Stein Point Markov chain Monte\nCarlo, and Stein variational gradient descent following Riabiz\net al. (2022) , Chen et al.\n(2018) , Chen et al. (2019)\n, and Liu and Wang (2016)\n. Gaussian mixture utilities are\nincluded for simulation, likelihoods, posterior probabilities,\nscores, and plots.", "URL": "https://github.com/junhao7622/steinsampling", "BugReports": "https://github.com/junhao7622/steinsampling/issues", "License": "GPL (>= 2)", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "Collate": "'steinsampling-package.R' 'stein_helpers.R' 'kernel_classes.R'\n'bootstrap.R' 'gmm_model.R' 'ksd_u_test.R' 'ksd_v_test.R'\n'fssd_test.R' 'svgd.R' 'stein_thinning.R' 'stein_points.R'\n'stein_point_mcmc.R'", "Config/testthat/edition": "3", "NeedsCompilation": "no", "Config/roxygen2/version": "8.0.0", "Repository": "https://junhao7622.r-universe.dev", "Date/Publication": "2026-07-12 05:55:49 UTC", "RemoteUrl": "https://github.com/junhao7622/steinsampling", "RemoteRef": "HEAD", "RemoteSha": "4ba336054ae37035234902d2f4e27844c6cbf184", "Packaged": { "Date": "2026-07-22 07:37:45 UTC", "User": "root" }, "Author": "Junhao Gao [aut, cre],\nEry Arias-Castro [aut]", 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