{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:2TOLXUN53FLTDYLIKHAIPTHIVT","short_pith_number":"pith:2TOLXUN5","schema_version":"1.0","canonical_sha256":"d4dcbbd1bdd95731e16851c087cce8acdacafe63479015130bd78340b007e81c","source":{"kind":"arxiv","id":"1605.03508","version":2},"attestation_state":"computed","paper":{"title":"A Poisson process reparameterisation for Bayesian inference for extremes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Jonathan A. Tawn, Paul Sharkey","submitted_at":"2016-05-11T16:51:00Z","abstract_excerpt":"A common approach to modelling extreme values is to consider the excesses above a high threshold as realisations of a non-homogeneous Poisson process. While this method offers the advantage of modelling using threshold-invariant extreme value parameters, the dependence between these parameters makes estimation more difficult. We present a novel approach for Bayesian estimation of the Poisson process model parameters by reparameterising in terms of a tuning parameter $m$. This paper presents a method for choosing the optimal value of m that near-orthogonalises the parameters, which is achieved "},"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":"1605.03508","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.AP","submitted_at":"2016-05-11T16:51:00Z","cross_cats_sorted":[],"title_canon_sha256":"76989bf40d501b5495c2b486de93b989fc75f90d060819a52fb6dcf982c749b1","abstract_canon_sha256":"e9ac56b08648bb9b9a76fc210c8865814ad6e399c769322e1ee58bafe02be219"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:55:34.236897Z","signature_b64":"haq35yiTfjG0OiktzNeLWVmN62kaSQB5w0ywxcanmvntMXpD2X9jhywu589V+bB/2QunT3zoIFZIlCuyIVfoBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d4dcbbd1bdd95731e16851c087cce8acdacafe63479015130bd78340b007e81c","last_reissued_at":"2026-05-18T00:55:34.236326Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:55:34.236326Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Poisson process reparameterisation for Bayesian inference for extremes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Jonathan A. Tawn, Paul Sharkey","submitted_at":"2016-05-11T16:51:00Z","abstract_excerpt":"A common approach to modelling extreme values is to consider the excesses above a high threshold as realisations of a non-homogeneous Poisson process. While this method offers the advantage of modelling using threshold-invariant extreme value parameters, the dependence between these parameters makes estimation more difficult. We present a novel approach for Bayesian estimation of the Poisson process model parameters by reparameterising in terms of a tuning parameter $m$. This paper presents a method for choosing the optimal value of m that near-orthogonalises the parameters, which is achieved "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.03508","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":"1605.03508","created_at":"2026-05-18T00:55:34.236410+00:00"},{"alias_kind":"arxiv_version","alias_value":"1605.03508v2","created_at":"2026-05-18T00:55:34.236410+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.03508","created_at":"2026-05-18T00:55:34.236410+00:00"},{"alias_kind":"pith_short_12","alias_value":"2TOLXUN53FLT","created_at":"2026-05-18T12:29:55.572404+00:00"},{"alias_kind":"pith_short_16","alias_value":"2TOLXUN53FLTDYLI","created_at":"2026-05-18T12:29:55.572404+00:00"},{"alias_kind":"pith_short_8","alias_value":"2TOLXUN5","created_at":"2026-05-18T12:29:55.572404+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/2TOLXUN53FLTDYLIKHAIPTHIVT","json":"https://pith.science/pith/2TOLXUN53FLTDYLIKHAIPTHIVT.json","graph_json":"https://pith.science/api/pith-number/2TOLXUN53FLTDYLIKHAIPTHIVT/graph.json","events_json":"https://pith.science/api/pith-number/2TOLXUN53FLTDYLIKHAIPTHIVT/events.json","paper":"https://pith.science/paper/2TOLXUN5"},"agent_actions":{"view_html":"https://pith.science/pith/2TOLXUN53FLTDYLIKHAIPTHIVT","download_json":"https://pith.science/pith/2TOLXUN53FLTDYLIKHAIPTHIVT.json","view_paper":"https://pith.science/paper/2TOLXUN5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1605.03508&json=true","fetch_graph":"https://pith.science/api/pith-number/2TOLXUN53FLTDYLIKHAIPTHIVT/graph.json","fetch_events":"https://pith.science/api/pith-number/2TOLXUN53FLTDYLIKHAIPTHIVT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2TOLXUN53FLTDYLIKHAIPTHIVT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2TOLXUN53FLTDYLIKHAIPTHIVT/action/storage_attestation","attest_author":"https://pith.science/pith/2TOLXUN53FLTDYLIKHAIPTHIVT/action/author_attestation","sign_citation":"https://pith.science/pith/2TOLXUN53FLTDYLIKHAIPTHIVT/action/citation_signature","submit_replication":"https://pith.science/pith/2TOLXUN53FLTDYLIKHAIPTHIVT/action/replication_record"}},"created_at":"2026-05-18T00:55:34.236410+00:00","updated_at":"2026-05-18T00:55:34.236410+00:00"}