{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:U2FGRRK2B72ENXME3EAY2GMNBC","short_pith_number":"pith:U2FGRRK2","schema_version":"1.0","canonical_sha256":"a68a68c55a0ff446dd84d9018d198d08a60448f22c7747767338177920072b7e","source":{"kind":"arxiv","id":"1603.04189","version":2},"attestation_state":"computed","paper":{"title":"A Change-Point Model for Detecting Heterogeneity in Ordered Survival Responses","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Gr\\'egory Nuel (LPMA), Olivier Bouaziz (MAP5)","submitted_at":"2016-03-14T10:25:59Z","abstract_excerpt":"In this article we suggest a new statistical approach considering survival heterogeneity as a breakpoint model in an ordered sequence of time to event variables. The survival responses need to be ordered according to a numerical covariate. Our esti- mation method will aim at detecting heterogeneity that could arise through the or- dering covariate. We formally introduce our model as a constrained Hidden Markov Model (HMM) where the hidden states are the unknown segmentation (breakpoint locations) and the observed states are the survival responses. We derive an efficient Expectation-Maximizatio"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1603.04189","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2016-03-14T10:25:59Z","cross_cats_sorted":[],"title_canon_sha256":"385c17517ebc4d85ad0f0d84da30bb927348f2a03e6f564080cac659df2cda6b","abstract_canon_sha256":"5bc3430840257b5882aea8bbfa5e707e7d20b51546a0ba460b24a34233f14135"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:04:04.029665Z","signature_b64":"Wj1f5U6NncH26cEcRG/Jov78eT216nMtssQnhEQxpMwpXy/0WmWe5N+ShTxYZLvzAWBDR8phCkxmhAVeo4izBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a68a68c55a0ff446dd84d9018d198d08a60448f22c7747767338177920072b7e","last_reissued_at":"2026-05-18T01:04:04.029010Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:04:04.029010Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Change-Point Model for Detecting Heterogeneity in Ordered Survival Responses","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Gr\\'egory Nuel (LPMA), Olivier Bouaziz (MAP5)","submitted_at":"2016-03-14T10:25:59Z","abstract_excerpt":"In this article we suggest a new statistical approach considering survival heterogeneity as a breakpoint model in an ordered sequence of time to event variables. The survival responses need to be ordered according to a numerical covariate. Our esti- mation method will aim at detecting heterogeneity that could arise through the or- dering covariate. We formally introduce our model as a constrained Hidden Markov Model (HMM) where the hidden states are the unknown segmentation (breakpoint locations) and the observed states are the survival responses. We derive an efficient Expectation-Maximizatio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.04189","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1603.04189","created_at":"2026-05-18T01:04:04.029102+00:00"},{"alias_kind":"arxiv_version","alias_value":"1603.04189v2","created_at":"2026-05-18T01:04:04.029102+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.04189","created_at":"2026-05-18T01:04:04.029102+00:00"},{"alias_kind":"pith_short_12","alias_value":"U2FGRRK2B72E","created_at":"2026-05-18T12:30:46.583412+00:00"},{"alias_kind":"pith_short_16","alias_value":"U2FGRRK2B72ENXME","created_at":"2026-05-18T12:30:46.583412+00:00"},{"alias_kind":"pith_short_8","alias_value":"U2FGRRK2","created_at":"2026-05-18T12:30:46.583412+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/U2FGRRK2B72ENXME3EAY2GMNBC","json":"https://pith.science/pith/U2FGRRK2B72ENXME3EAY2GMNBC.json","graph_json":"https://pith.science/api/pith-number/U2FGRRK2B72ENXME3EAY2GMNBC/graph.json","events_json":"https://pith.science/api/pith-number/U2FGRRK2B72ENXME3EAY2GMNBC/events.json","paper":"https://pith.science/paper/U2FGRRK2"},"agent_actions":{"view_html":"https://pith.science/pith/U2FGRRK2B72ENXME3EAY2GMNBC","download_json":"https://pith.science/pith/U2FGRRK2B72ENXME3EAY2GMNBC.json","view_paper":"https://pith.science/paper/U2FGRRK2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1603.04189&json=true","fetch_graph":"https://pith.science/api/pith-number/U2FGRRK2B72ENXME3EAY2GMNBC/graph.json","fetch_events":"https://pith.science/api/pith-number/U2FGRRK2B72ENXME3EAY2GMNBC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/U2FGRRK2B72ENXME3EAY2GMNBC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/U2FGRRK2B72ENXME3EAY2GMNBC/action/storage_attestation","attest_author":"https://pith.science/pith/U2FGRRK2B72ENXME3EAY2GMNBC/action/author_attestation","sign_citation":"https://pith.science/pith/U2FGRRK2B72ENXME3EAY2GMNBC/action/citation_signature","submit_replication":"https://pith.science/pith/U2FGRRK2B72ENXME3EAY2GMNBC/action/replication_record"}},"created_at":"2026-05-18T01:04:04.029102+00:00","updated_at":"2026-05-18T01:04:04.029102+00:00"}