{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:ADD4MAXMZCUQWQSBMQT6SSZ2B2","short_pith_number":"pith:ADD4MAXM","schema_version":"1.0","canonical_sha256":"00c7c602ecc8a90b42416427e94b3a0e994224e86870b319279e126b65763395","source":{"kind":"arxiv","id":"2409.10174","version":2},"attestation_state":"computed","paper":{"title":"Information criteria for the number of directions of extremes in high-dimensional data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Lucas Butsch, Vicky Fasen-Hartmann","submitted_at":"2024-09-16T11:10:42Z","abstract_excerpt":"In multivariate extreme value analysis, the estimation of the dependence structure in extremes is demanding, especially in the context of high-dimensional data. Therefore, a common approach is to reduce the model dimension by considering only the directions in which extreme values occur. In this paper, we use the concept of sparse regular variation recently introduced by Meyer and Wintenberger (2021) to derive information criteria for the number of directions in which extreme events occur, such as a Bayesian information criterion (BIC), a mean-squared error-based information criterion (MSEIC),"},"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":"2409.10174","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2024-09-16T11:10:42Z","cross_cats_sorted":[],"title_canon_sha256":"84d73ee9bcf9d8bf03c421c52f1200baa1ad57258793b468787ea64ff14e6a76","abstract_canon_sha256":"808d1477073a73ec228efba587a11678e0c267b077ceb1a5dc24aa0f22c4c5b6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:31:40.012630Z","signature_b64":"fPIMoLXYKCflpqdoDnaHVh7BQyJ0g2k8hefyjAnfHgZbDnXJv4N7FuuTzzbpjBiGHr16Br5+3IO0SmatiiiaBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"00c7c602ecc8a90b42416427e94b3a0e994224e86870b319279e126b65763395","last_reissued_at":"2026-07-05T11:31:40.012117Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:31:40.012117Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Information criteria for the number of directions of extremes in high-dimensional data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Lucas Butsch, Vicky Fasen-Hartmann","submitted_at":"2024-09-16T11:10:42Z","abstract_excerpt":"In multivariate extreme value analysis, the estimation of the dependence structure in extremes is demanding, especially in the context of high-dimensional data. Therefore, a common approach is to reduce the model dimension by considering only the directions in which extreme values occur. In this paper, we use the concept of sparse regular variation recently introduced by Meyer and Wintenberger (2021) to derive information criteria for the number of directions in which extreme events occur, such as a Bayesian information criterion (BIC), a mean-squared error-based information criterion (MSEIC),"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.10174","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2409.10174/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2409.10174","created_at":"2026-07-05T11:31:40.012182+00:00"},{"alias_kind":"arxiv_version","alias_value":"2409.10174v2","created_at":"2026-07-05T11:31:40.012182+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.10174","created_at":"2026-07-05T11:31:40.012182+00:00"},{"alias_kind":"pith_short_12","alias_value":"ADD4MAXMZCUQ","created_at":"2026-07-05T11:31:40.012182+00:00"},{"alias_kind":"pith_short_16","alias_value":"ADD4MAXMZCUQWQSB","created_at":"2026-07-05T11:31:40.012182+00:00"},{"alias_kind":"pith_short_8","alias_value":"ADD4MAXM","created_at":"2026-07-05T11:31:40.012182+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.07213","citing_title":"Principal Component Analysis for Multivariate Extremes","ref_index":4,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ADD4MAXMZCUQWQSBMQT6SSZ2B2","json":"https://pith.science/pith/ADD4MAXMZCUQWQSBMQT6SSZ2B2.json","graph_json":"https://pith.science/api/pith-number/ADD4MAXMZCUQWQSBMQT6SSZ2B2/graph.json","events_json":"https://pith.science/api/pith-number/ADD4MAXMZCUQWQSBMQT6SSZ2B2/events.json","paper":"https://pith.science/paper/ADD4MAXM"},"agent_actions":{"view_html":"https://pith.science/pith/ADD4MAXMZCUQWQSBMQT6SSZ2B2","download_json":"https://pith.science/pith/ADD4MAXMZCUQWQSBMQT6SSZ2B2.json","view_paper":"https://pith.science/paper/ADD4MAXM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2409.10174&json=true","fetch_graph":"https://pith.science/api/pith-number/ADD4MAXMZCUQWQSBMQT6SSZ2B2/graph.json","fetch_events":"https://pith.science/api/pith-number/ADD4MAXMZCUQWQSBMQT6SSZ2B2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ADD4MAXMZCUQWQSBMQT6SSZ2B2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ADD4MAXMZCUQWQSBMQT6SSZ2B2/action/storage_attestation","attest_author":"https://pith.science/pith/ADD4MAXMZCUQWQSBMQT6SSZ2B2/action/author_attestation","sign_citation":"https://pith.science/pith/ADD4MAXMZCUQWQSBMQT6SSZ2B2/action/citation_signature","submit_replication":"https://pith.science/pith/ADD4MAXMZCUQWQSBMQT6SSZ2B2/action/replication_record"}},"created_at":"2026-07-05T11:31:40.012182+00:00","updated_at":"2026-07-05T11:31:40.012182+00:00"}