{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-linear-time-kernel-goodness-of-fit-test","title":"A Linear-Time Kernel Goodness-of-Fit Test","arxiv_id":"1705.07673","date":"2017-05-22","proceeding":"NeurIPS 2017 12","authors":["Wittawat Jitkrittum","Wenkai Xu","Zoltan Szabo","Kenji Fukumizu","Arthur Gretton"],"abstract":"We propose a novel adaptive test of goodness-of-fit, with computational cost\nlinear in the number of samples. We learn the test features that best indicate\nthe differences between observed samples and a reference model, by minimizing\nthe false negative rate. These features are constructed via Stein's method,\nmeaning that it is not necessary to compute the normalising constant of the\nmodel. We analyse the asymptotic Bahadur efficiency of the new test, and prove\nthat under a mean-shift alternative, our test always has greater relative\nefficiency than a previous linear-time kernel test, regardless of the choice of\nparameters for that test. In experiments, the performance of our method exceeds\nthat of the earlier linear-time test, and matches or exceeds the power of a\nquadratic-time kernel test. In high dimensions and where model structure may be\nexploited, our goodness of fit test performs far better than a quadratic-time\ntwo-sample test based on the Maximum Mean Discrepancy, with samples drawn from\nthe model.","url_abs":"http://arxiv.org/abs/1705.07673v2","url_pdf":"http://arxiv.org/pdf/1705.07673v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-linear-time-kernel-goodness-of-fit-test","repo_url":"https://github.com/wittawatj/kernel-gof","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"a-linear-time-kernel-goodness-of-fit-test","repo_url":"https://github.com/jenninglim/model-comparison-test","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"a-linear-time-kernel-goodness-of-fit-test","repo_url":"https://github.com/jenninglim/multiscale-features","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"a-linear-time-kernel-goodness-of-fit-test","repo_url":"https://github.com/wittawatj/model-comparison-test","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1705.07673","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1705.07673"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/wittawatj/kernel-gof","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/jenninglim/multiscale-features","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/wittawatj/model-comparison-test","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/jenninglim/model-comparison-test","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"ran_fixture":1,"unverified":2},"by_repo_kind":{"official":{"samples":3,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"832f645fb23b391a","entry":"ex_result_folder","repo":"wittawatj/kernel-gof","repo_kind":"official","path":"kgof/glo.py","file_url":"https://github.com/wittawatj/kernel-gof/blob/HEAD/kgof/glo.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"DEP_MISSING","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"832f645fb23b391a"}},{"code_sha256_prefix":"9d9d13454e89689c","entry":"ex_load_result","repo":"wittawatj/kernel-gof","repo_kind":"official","path":"kgof/glo.py","file_url":"https://github.com/wittawatj/kernel-gof/blob/HEAD/kgof/glo.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"9d9d13454e89689c"}},{"code_sha256_prefix":"f26874776edab1a6","entry":"ex_result_file","repo":"wittawatj/kernel-gof","repo_kind":"official","path":"kgof/glo.py","file_url":"https://github.com/wittawatj/kernel-gof/blob/HEAD/kgof/glo.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"f26874776edab1a6"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}