{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:PDGVUKLMDRSBUVKTFRVLZZSZ6V","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"df796e4dd741e26f245da02e814d4a39d5d13f621e886f6126cc3d2eb498d367","cross_cats_sorted":["math.ST","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-02-03T15:30:18Z","title_canon_sha256":"731d150a157970ddf3d40f42c15e6b16a7f5ffad5a335a32db348c0e0e0fce14"},"schema_version":"1.0","source":{"id":"2402.02187","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.02187","created_at":"2026-07-05T07:41:12Z"},{"alias_kind":"arxiv_version","alias_value":"2402.02187v1","created_at":"2026-07-05T07:41:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.02187","created_at":"2026-07-05T07:41:12Z"},{"alias_kind":"pith_short_12","alias_value":"PDGVUKLMDRSB","created_at":"2026-07-05T07:41:12Z"},{"alias_kind":"pith_short_16","alias_value":"PDGVUKLMDRSBUVKT","created_at":"2026-07-05T07:41:12Z"},{"alias_kind":"pith_short_8","alias_value":"PDGVUKLM","created_at":"2026-07-05T07:41:12Z"}],"graph_snapshots":[{"event_id":"sha256:097d3ebb793907b25801e23ab4b47b64015b2271ef0bea53ec884f77d141779a","target":"graph","created_at":"2026-07-05T07:41:12Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2402.02187/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graphical models in extremes have emerged as a diverse and quickly expanding research area in extremal dependence modeling. They allow for parsimonious statistical methodology and are particularly suited for enforcing sparsity in high-dimensional problems. In this work, we provide the fundamental concepts of extremal graphical models and discuss recent advances in the field. Different existing perspectives on graphical extremes are presented in a unified way through graphical models for exponent measures. We discuss the important cases of nonparametric extremal graphical models on simple graph","authors_text":"Frank R\\\"ottger, Manuel Hentschel, Micha\\\"el Lalancette, Sebastian Engelke","cross_cats":["math.ST","stat.TH"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-02-03T15:30:18Z","title":"Graphical models for multivariate extremes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.02187","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:273e653feb064ec7c39f53fc50767d3afc2b3111a0deac4b2852d73da13db0fe","target":"record","created_at":"2026-07-05T07:41:12Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"df796e4dd741e26f245da02e814d4a39d5d13f621e886f6126cc3d2eb498d367","cross_cats_sorted":["math.ST","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-02-03T15:30:18Z","title_canon_sha256":"731d150a157970ddf3d40f42c15e6b16a7f5ffad5a335a32db348c0e0e0fce14"},"schema_version":"1.0","source":{"id":"2402.02187","kind":"arxiv","version":1}},"canonical_sha256":"78cd5a296c1c641a55532c6abce659f54de62f9cf197cad446e389a69e261b79","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"78cd5a296c1c641a55532c6abce659f54de62f9cf197cad446e389a69e261b79","first_computed_at":"2026-07-05T07:41:12.005057Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:41:12.005057Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"M7rjE/spOxck3GOnrOh3hmyDsGxvgpHjvxRT4F0ILgaLlhYaRZge/gn7Ip4bJm4fI+4JmCNitQl8+PYY+FNoDA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:41:12.005525Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.02187","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:273e653feb064ec7c39f53fc50767d3afc2b3111a0deac4b2852d73da13db0fe","sha256:097d3ebb793907b25801e23ab4b47b64015b2271ef0bea53ec884f77d141779a"],"state_sha256":"11d33c2194b1f8aba98ea032cd1dcd34ac3b3ebc8bb68367c46c83af020f310b"}