{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:BSAWYPEJXQLJI77GD6OLUMLLE2","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"0f9f6f0a6982ce8f0617694e91bc8ca8d3ccc53d76dcfa10f8c9bd8147baca74","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2026-05-15T10:09:49Z","title_canon_sha256":"a913d227e8f0649f72679a8a3290f9dfb41d2ba8774c3c613752dd7a3bf89e2d"},"schema_version":"1.0","source":{"id":"2605.15814","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.15814","created_at":"2026-05-20T00:01:19Z"},{"alias_kind":"arxiv_version","alias_value":"2605.15814v1","created_at":"2026-05-20T00:01:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.15814","created_at":"2026-05-20T00:01:19Z"},{"alias_kind":"pith_short_12","alias_value":"BSAWYPEJXQLJ","created_at":"2026-05-20T00:01:19Z"},{"alias_kind":"pith_short_16","alias_value":"BSAWYPEJXQLJI77G","created_at":"2026-05-20T00:01:19Z"},{"alias_kind":"pith_short_8","alias_value":"BSAWYPEJ","created_at":"2026-05-20T00:01:19Z"}],"graph_snapshots":[{"event_id":"sha256:d96025d9e4377a50bda4f50d9e1850b5abcf6804b026ffc2f27e02f0fbaea58f","target":"graph","created_at":"2026-05-20T00:01:19Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"We propose a novel approach to conducting such goodness-of-fit tests. The idea is to construct a unitary transformation of a natural parametric testing process such that it converges weakly to a ``standard'' target process, independent of the particular parametric form assumed under the null hypothesis. This transformation therefore paves the way for asymptotically distribution-free goodness-of-fit testing of parametric point processes."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"The assumption that a unitary transformation exists which maps the natural parametric testing process to a limiting target whose distribution is completely free of the unknown parameters in the intensity family; this premise is invoked when the abstract states that the transformed process converges weakly to a standard target independent of the parametric form."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"A unitary transformation is introduced for parametric testing processes in point processes to enable asymptotically distribution-free goodness-of-fit tests."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"A unitary transformation maps the natural testing process for parametric point processes to a limiting target whose distribution is free of unknown intensity parameters."}],"snapshot_sha256":"b1bf411d1d85b30d1c992ab6baf50564dad19f208435fe66375f359d5f7eb274"},"formal_canon":{"evidence_count":2,"snapshot_sha256":"e3dac435f23244416c3832d82161c142992937ab41e9ed05a5336f538991c367"},"integrity":{"available":true,"clean":true,"detectors_run":[{"findings_count":0,"name":"doi_title_agreement","ran_at":"2026-05-19T20:01:19.139197Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"doi_compliance","ran_at":"2026-05-19T19:50:55.504073Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T17:33:48.729056Z","status":"skipped","version":"1.0.0"},{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T17:21:55.883571Z","status":"completed","version":"1.0.0"}],"endpoint":"/pith/2605.15814/integrity.json","findings":[],"snapshot_sha256":"e0a921ebda0126689d658a3fef91f051999d9d2f6c7ba7f12f694f8f7b920287","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Suppose we have an observed path from a point process counting event occurrences in a large population. Based on the observed path, we would like to test the null hypothesis that the conditional intensity of the point process belongs to a particular parametric family. We propose a novel approach to conducting such goodness-of-fit tests. The idea is to construct a unitary transformation of a natural parametric testing process such that it converges weakly to a ``standard'' target process, independent of the particular parametric form assumed under the null hypothesis. This transformation theref","authors_text":"Estate V. Khmaladze, Roger J. A. Laeven, Sami Umut Can","cross_cats":["stat.TH"],"headline":"A unitary transformation maps the natural testing process for parametric point processes to a limiting target whose distribution is free of unknown intensity parameters.","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2026-05-15T10:09:49Z","title":"Goodness-of-Fit Testing for Point Processes in Large Populations"},"references":{"count":70,"internal_anchors":0,"resolved_work":70,"sample":[{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":1,"title":"2002 , PUBLISHER =","work_id":"f5080a4a-97b3-4d61-9bf0-53a2c4d95201","year":2002},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":2,"title":"1996 , PUBLISHER =","work_id":"d77a5309-6989-4eb2-a390-19ce529bc3b5","year":1996},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":3,"title":"2007 , PUBLISHER =","work_id":"b57502ba-5f3a-46fe-a1af-420e9970a7f6","year":2007},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":4,"title":"Lin, D. and Wei, L.-J. and Ying, Z. , JOURNAL =. Checking the","work_id":"6fa10a3e-7084-43e7-a7e8-5bf2e1df1764","year":null},{"cited_arxiv_id":"","doi":"","is_internal_anchor":false,"ref_index":5,"title":"and Dobler, Dennis and de Gunst, Mathisca C","work_id":"13af54bf-4519-45a7-aa85-7c5db1fb8691","year":null}],"snapshot_sha256":"04424219b174712246b1db9314f98dc37b4ac360e42c9186eda8d56069224970"},"source":{"id":"2605.15814","kind":"arxiv","version":1},"verdict":{"created_at":"2026-05-19T19:42:32.873412Z","id":"91f67521-fde8-4ba2-94bd-56515967fac9","model_set":{"reader":"grok-4.3"},"one_line_summary":"A unitary transformation is introduced for parametric testing processes in point processes to enable asymptotically distribution-free goodness-of-fit tests.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"A unitary transformation maps the natural testing process for parametric point processes to a limiting target whose distribution is free of unknown intensity parameters.","strongest_claim":"We propose a novel approach to conducting such goodness-of-fit tests. The idea is to construct a unitary transformation of a natural parametric testing process such that it converges weakly to a ``standard'' target process, independent of the particular parametric form assumed under the null hypothesis. This transformation therefore paves the way for asymptotically distribution-free goodness-of-fit testing of parametric point processes.","weakest_assumption":"The assumption that a unitary transformation exists which maps the natural parametric testing process to a limiting target whose distribution is completely free of the unknown parameters in the intensity family; this premise is invoked when the abstract states that the transformed process converges weakly to a standard target independent of the parametric form."}},"verdict_id":"91f67521-fde8-4ba2-94bd-56515967fac9"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:6b554702da0da940596186c497d999778fc4f52456d8f60f2f0c657b4faac4b7","target":"record","created_at":"2026-05-20T00:01:19Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"0f9f6f0a6982ce8f0617694e91bc8ca8d3ccc53d76dcfa10f8c9bd8147baca74","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2026-05-15T10:09:49Z","title_canon_sha256":"a913d227e8f0649f72679a8a3290f9dfb41d2ba8774c3c613752dd7a3bf89e2d"},"schema_version":"1.0","source":{"id":"2605.15814","kind":"arxiv","version":1}},"canonical_sha256":"0c816c3c89bc16947fe61f9cba316b26897d4534cb2b23ed2c5c6db8a04ea631","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0c816c3c89bc16947fe61f9cba316b26897d4534cb2b23ed2c5c6db8a04ea631","first_computed_at":"2026-05-20T00:01:19.922142Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:01:19.922142Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ss7Iz8No6eckjNeUJsiq2c3JjEguyD+AAGIBvTh0y5P3hTGHeXe43FAndZbX57ccOYqtYjYEaNrkYN1EsRxmDQ==","signature_status":"signed_v1","signed_at":"2026-05-20T00:01:19.923704Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.15814","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6b554702da0da940596186c497d999778fc4f52456d8f60f2f0c657b4faac4b7","sha256:d96025d9e4377a50bda4f50d9e1850b5abcf6804b026ffc2f27e02f0fbaea58f"],"state_sha256":"f626286db07267a11bc65c128cc7a356c23d82fba5a1954fe38e841fbc0cfb4a"}