{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:TPCAXS5FDGFOFPNHX4FCFKYTIJ","short_pith_number":"pith:TPCAXS5F","schema_version":"1.0","canonical_sha256":"9bc40bcba5198ae2bda7bf0a22ab1342507c46e2396b91d1213653344cc320d2","source":{"kind":"arxiv","id":"1905.07912","version":1},"attestation_state":"computed","paper":{"title":"Semiparametric estimation for space-time max-stable processes: F -madogram-based estimation approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.PR","stat.AP"],"primary_cat":"stat.ME","authors_text":"Abdul-Fattah Abu-Awwad (ICJ, ICJ), Pierre Ribereau (PSPM, PSPM), V\\'eronique Maume-Deschamps (ICJ","submitted_at":"2019-05-20T07:04:38Z","abstract_excerpt":"Max-stable processes have been expanded to quantify extremal dependence in spatio-temporal data. Due to the interaction between space and time, spatio-temporal data are often complex to analyze. So, characterizing these dependencies is one of the crucial challenges in this field of statistics. This paper suggests a semiparametric inference methodology based on the spatio-temporal F-madogram for estimating the parameters of a space-time max-stable process using gridded data. The performance of the method is investigated through various simulation studies. Finally, we apply our inferential proce"},"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":"1905.07912","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2019-05-20T07:04:38Z","cross_cats_sorted":["math.PR","stat.AP"],"title_canon_sha256":"bbcab00229b0613eb552ddcbc17acef4193ae3380c93f3b9bcf2d40bad800d89","abstract_canon_sha256":"2b2571ef8172f2d2cad41dadfba21fa869ef5794e984b2d03ec95d04d1f3ed5f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:45:48.123972Z","signature_b64":"DyTkU7mxV38VmCakciqIw1I65K8cbWWKSr7FuPRfuxY/l38PxQ6vp6sOJAbP0DybtSfp6WyiZ7f+EnWzAsNkBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9bc40bcba5198ae2bda7bf0a22ab1342507c46e2396b91d1213653344cc320d2","last_reissued_at":"2026-05-17T23:45:48.123193Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:45:48.123193Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Semiparametric estimation for space-time max-stable processes: F -madogram-based estimation approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.PR","stat.AP"],"primary_cat":"stat.ME","authors_text":"Abdul-Fattah Abu-Awwad (ICJ, ICJ), Pierre Ribereau (PSPM, PSPM), V\\'eronique Maume-Deschamps (ICJ","submitted_at":"2019-05-20T07:04:38Z","abstract_excerpt":"Max-stable processes have been expanded to quantify extremal dependence in spatio-temporal data. Due to the interaction between space and time, spatio-temporal data are often complex to analyze. So, characterizing these dependencies is one of the crucial challenges in this field of statistics. This paper suggests a semiparametric inference methodology based on the spatio-temporal F-madogram for estimating the parameters of a space-time max-stable process using gridded data. The performance of the method is investigated through various simulation studies. Finally, we apply our inferential proce"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.07912","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":"1905.07912","created_at":"2026-05-17T23:45:48.123332+00:00"},{"alias_kind":"arxiv_version","alias_value":"1905.07912v1","created_at":"2026-05-17T23:45:48.123332+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.07912","created_at":"2026-05-17T23:45:48.123332+00:00"},{"alias_kind":"pith_short_12","alias_value":"TPCAXS5FDGFO","created_at":"2026-05-18T12:33:30.264802+00:00"},{"alias_kind":"pith_short_16","alias_value":"TPCAXS5FDGFOFPNH","created_at":"2026-05-18T12:33:30.264802+00:00"},{"alias_kind":"pith_short_8","alias_value":"TPCAXS5F","created_at":"2026-05-18T12:33:30.264802+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/TPCAXS5FDGFOFPNHX4FCFKYTIJ","json":"https://pith.science/pith/TPCAXS5FDGFOFPNHX4FCFKYTIJ.json","graph_json":"https://pith.science/api/pith-number/TPCAXS5FDGFOFPNHX4FCFKYTIJ/graph.json","events_json":"https://pith.science/api/pith-number/TPCAXS5FDGFOFPNHX4FCFKYTIJ/events.json","paper":"https://pith.science/paper/TPCAXS5F"},"agent_actions":{"view_html":"https://pith.science/pith/TPCAXS5FDGFOFPNHX4FCFKYTIJ","download_json":"https://pith.science/pith/TPCAXS5FDGFOFPNHX4FCFKYTIJ.json","view_paper":"https://pith.science/paper/TPCAXS5F","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1905.07912&json=true","fetch_graph":"https://pith.science/api/pith-number/TPCAXS5FDGFOFPNHX4FCFKYTIJ/graph.json","fetch_events":"https://pith.science/api/pith-number/TPCAXS5FDGFOFPNHX4FCFKYTIJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TPCAXS5FDGFOFPNHX4FCFKYTIJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TPCAXS5FDGFOFPNHX4FCFKYTIJ/action/storage_attestation","attest_author":"https://pith.science/pith/TPCAXS5FDGFOFPNHX4FCFKYTIJ/action/author_attestation","sign_citation":"https://pith.science/pith/TPCAXS5FDGFOFPNHX4FCFKYTIJ/action/citation_signature","submit_replication":"https://pith.science/pith/TPCAXS5FDGFOFPNHX4FCFKYTIJ/action/replication_record"}},"created_at":"2026-05-17T23:45:48.123332+00:00","updated_at":"2026-05-17T23:45:48.123332+00:00"}