{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:M3TFQQEHMPOG2N2SGHCYKEJORC","short_pith_number":"pith:M3TFQQEH","schema_version":"1.0","canonical_sha256":"66e658408763dc6d375231c585112e88b896736db6089ac9d2f46c74187dc368","source":{"kind":"arxiv","id":"1504.00465","version":1},"attestation_state":"computed","paper":{"title":"Asymptotically distribution-free goodness-of-fit testing for tail copulas","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Estate V. Khmaladze, John H. J. Einmahl, Roger J. A. Laeven, Sami Umut Can","submitted_at":"2015-04-02T07:56:51Z","abstract_excerpt":"Let $(X_1,Y_1),\\ldots,(X_n,Y_n)$ be an i.i.d. sample from a bivariate distribution function that lies in the max-domain of attraction of an extreme value distribution. The asymptotic joint distribution of the standardized component-wise maxima $\\bigvee_{i=1}^nX_i$ and $\\bigvee_{i=1}^nY_i$ is then characterized by the marginal extreme value indices and the tail copula $R$. We propose a procedure for constructing asymptotically distribution-free goodness-of-fit tests for the tail copula $R$. The procedure is based on a transformation of a suitable empirical process derived from a semi-parametric"},"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":"1504.00465","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2015-04-02T07:56:51Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"67327572ea01a89ff76f40c37fe4e851363734b5c8d0b2cf4f702c53658e2505","abstract_canon_sha256":"d79cf3bbe36f3f7b47e744ec2be057d7db2e3481547f8338209512ce79535303"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:19:43.241014Z","signature_b64":"QnACErmHswtgbhTBmD5c1pe6TSEBkT30b7LLEcnudL/X862raLfwjIVw98KhEaKbFZ6iYeOnn/Z3AwyeUHXZDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"66e658408763dc6d375231c585112e88b896736db6089ac9d2f46c74187dc368","last_reissued_at":"2026-05-18T02:19:43.240601Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:19:43.240601Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Asymptotically distribution-free goodness-of-fit testing for tail copulas","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Estate V. Khmaladze, John H. J. Einmahl, Roger J. A. Laeven, Sami Umut Can","submitted_at":"2015-04-02T07:56:51Z","abstract_excerpt":"Let $(X_1,Y_1),\\ldots,(X_n,Y_n)$ be an i.i.d. sample from a bivariate distribution function that lies in the max-domain of attraction of an extreme value distribution. The asymptotic joint distribution of the standardized component-wise maxima $\\bigvee_{i=1}^nX_i$ and $\\bigvee_{i=1}^nY_i$ is then characterized by the marginal extreme value indices and the tail copula $R$. We propose a procedure for constructing asymptotically distribution-free goodness-of-fit tests for the tail copula $R$. The procedure is based on a transformation of a suitable empirical process derived from a semi-parametric"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1504.00465","kind":"arxiv","version":1},"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":"1504.00465","created_at":"2026-05-18T02:19:43.240656+00:00"},{"alias_kind":"arxiv_version","alias_value":"1504.00465v1","created_at":"2026-05-18T02:19:43.240656+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1504.00465","created_at":"2026-05-18T02:19:43.240656+00:00"},{"alias_kind":"pith_short_12","alias_value":"M3TFQQEHMPOG","created_at":"2026-05-18T12:29:32.376354+00:00"},{"alias_kind":"pith_short_16","alias_value":"M3TFQQEHMPOG2N2S","created_at":"2026-05-18T12:29:32.376354+00:00"},{"alias_kind":"pith_short_8","alias_value":"M3TFQQEH","created_at":"2026-05-18T12:29:32.376354+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/M3TFQQEHMPOG2N2SGHCYKEJORC","json":"https://pith.science/pith/M3TFQQEHMPOG2N2SGHCYKEJORC.json","graph_json":"https://pith.science/api/pith-number/M3TFQQEHMPOG2N2SGHCYKEJORC/graph.json","events_json":"https://pith.science/api/pith-number/M3TFQQEHMPOG2N2SGHCYKEJORC/events.json","paper":"https://pith.science/paper/M3TFQQEH"},"agent_actions":{"view_html":"https://pith.science/pith/M3TFQQEHMPOG2N2SGHCYKEJORC","download_json":"https://pith.science/pith/M3TFQQEHMPOG2N2SGHCYKEJORC.json","view_paper":"https://pith.science/paper/M3TFQQEH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1504.00465&json=true","fetch_graph":"https://pith.science/api/pith-number/M3TFQQEHMPOG2N2SGHCYKEJORC/graph.json","fetch_events":"https://pith.science/api/pith-number/M3TFQQEHMPOG2N2SGHCYKEJORC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/M3TFQQEHMPOG2N2SGHCYKEJORC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/M3TFQQEHMPOG2N2SGHCYKEJORC/action/storage_attestation","attest_author":"https://pith.science/pith/M3TFQQEHMPOG2N2SGHCYKEJORC/action/author_attestation","sign_citation":"https://pith.science/pith/M3TFQQEHMPOG2N2SGHCYKEJORC/action/citation_signature","submit_replication":"https://pith.science/pith/M3TFQQEHMPOG2N2SGHCYKEJORC/action/replication_record"}},"created_at":"2026-05-18T02:19:43.240656+00:00","updated_at":"2026-05-18T02:19:43.240656+00:00"}