{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:23U5X5D4LOGUYQP3TB45AV2JLY","short_pith_number":"pith:23U5X5D4","canonical_record":{"source":{"id":"1902.09230","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-02-25T12:34:24Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"b6baa2ee7887190963b1b4cb5d97a32fb86301cca0088f409f13025e5c79639a","abstract_canon_sha256":"4e3a0b89d15cad7824536244e9a0ba17882f8d2692ddf8809041756477ee3291"},"schema_version":"1.0"},"canonical_sha256":"d6e9dbf47c5b8d4c41fb9879d057495e0d8156de8e7effb655468c8a5b5c1e91","source":{"kind":"arxiv","id":"1902.09230","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.09230","created_at":"2026-05-17T23:52:46Z"},{"alias_kind":"arxiv_version","alias_value":"1902.09230v1","created_at":"2026-05-17T23:52:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.09230","created_at":"2026-05-17T23:52:46Z"},{"alias_kind":"pith_short_12","alias_value":"23U5X5D4LOGU","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"23U5X5D4LOGUYQP3","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"23U5X5D4","created_at":"2026-05-18T12:33:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:23U5X5D4LOGUYQP3TB45AV2JLY","target":"record","payload":{"canonical_record":{"source":{"id":"1902.09230","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-02-25T12:34:24Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"b6baa2ee7887190963b1b4cb5d97a32fb86301cca0088f409f13025e5c79639a","abstract_canon_sha256":"4e3a0b89d15cad7824536244e9a0ba17882f8d2692ddf8809041756477ee3291"},"schema_version":"1.0"},"canonical_sha256":"d6e9dbf47c5b8d4c41fb9879d057495e0d8156de8e7effb655468c8a5b5c1e91","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:52:46.302183Z","signature_b64":"HwL1TsAYtPwTvUaFhv2zVf5B6nX6oHaewiiAB42I50swd9VMlOcIqCBcvPTxqqN/iraTDRdWCh6s1+3oYJNkDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6e9dbf47c5b8d4c41fb9879d057495e0d8156de8e7effb655468c8a5b5c1e91","last_reissued_at":"2026-05-17T23:52:46.301593Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:52:46.301593Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1902.09230","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:52:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kEs7ZOkka0Vjvmp8U7s9a0kuBwO9G4TfypJ6nagud0XDm8Ic42UCjRvP4u5+1DgAKwRT3zR66cSfsx0tns3XDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T23:31:04.765536Z"},"content_sha256":"c571a1730b067228ac30bd889bca5020442bd5a2e694f0f39c0c221a4f54da53","schema_version":"1.0","event_id":"sha256:c571a1730b067228ac30bd889bca5020442bd5a2e694f0f39c0c221a4f54da53"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:23U5X5D4LOGUYQP3TB45AV2JLY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sampling Sup-Normalized Spectral Functions for Brown-Resnick Processes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME","stat.TH"],"primary_cat":"math.ST","authors_text":"Claudia Schillings, Marco Oesting, Martin Schlather","submitted_at":"2019-02-25T12:34:24Z","abstract_excerpt":"Sup-normalized spectral functions form building blocks of max-stable and Pareto processes and therefore play an important role in modeling spatial extremes. For one of the most popular examples, the Brown-Resnick process, simulation is not straightforward. In this paper, we generalize two approaches for simulation via Markov Chain Monte Carlo methods and rejection sampling by introducing new classes of proposal densities. In both cases, we provide an optimal choice of the proposal density with respect to sampling efficiency. The performance of the procedures is demonstrated in an example."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.09230","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:52:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1J2GbnMd3qXDXmHOeCF1z4SrJBU1CU999YCGlLAlGx/GebdWeT+QAq411gpr4D0TrvopajyyZB+ddn9SyZI6BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T23:31:04.766197Z"},"content_sha256":"885ccca850654bfaea44308ee35fd37d90d481d56706f519aa0309fedd48a529","schema_version":"1.0","event_id":"sha256:885ccca850654bfaea44308ee35fd37d90d481d56706f519aa0309fedd48a529"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/23U5X5D4LOGUYQP3TB45AV2JLY/bundle.json","state_url":"https://pith.science/pith/23U5X5D4LOGUYQP3TB45AV2JLY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/23U5X5D4LOGUYQP3TB45AV2JLY/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-04T23:31:04Z","links":{"resolver":"https://pith.science/pith/23U5X5D4LOGUYQP3TB45AV2JLY","bundle":"https://pith.science/pith/23U5X5D4LOGUYQP3TB45AV2JLY/bundle.json","state":"https://pith.science/pith/23U5X5D4LOGUYQP3TB45AV2JLY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/23U5X5D4LOGUYQP3TB45AV2JLY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:23U5X5D4LOGUYQP3TB45AV2JLY","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":"4e3a0b89d15cad7824536244e9a0ba17882f8d2692ddf8809041756477ee3291","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-02-25T12:34:24Z","title_canon_sha256":"b6baa2ee7887190963b1b4cb5d97a32fb86301cca0088f409f13025e5c79639a"},"schema_version":"1.0","source":{"id":"1902.09230","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.09230","created_at":"2026-05-17T23:52:46Z"},{"alias_kind":"arxiv_version","alias_value":"1902.09230v1","created_at":"2026-05-17T23:52:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.09230","created_at":"2026-05-17T23:52:46Z"},{"alias_kind":"pith_short_12","alias_value":"23U5X5D4LOGU","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"23U5X5D4LOGUYQP3","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"23U5X5D4","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:885ccca850654bfaea44308ee35fd37d90d481d56706f519aa0309fedd48a529","target":"graph","created_at":"2026-05-17T23:52:46Z","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"},"paper":{"abstract_excerpt":"Sup-normalized spectral functions form building blocks of max-stable and Pareto processes and therefore play an important role in modeling spatial extremes. For one of the most popular examples, the Brown-Resnick process, simulation is not straightforward. In this paper, we generalize two approaches for simulation via Markov Chain Monte Carlo methods and rejection sampling by introducing new classes of proposal densities. In both cases, we provide an optimal choice of the proposal density with respect to sampling efficiency. The performance of the procedures is demonstrated in an example.","authors_text":"Claudia Schillings, Marco Oesting, Martin Schlather","cross_cats":["stat.ME","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-02-25T12:34:24Z","title":"Sampling Sup-Normalized Spectral Functions for Brown-Resnick Processes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.09230","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:c571a1730b067228ac30bd889bca5020442bd5a2e694f0f39c0c221a4f54da53","target":"record","created_at":"2026-05-17T23:52:46Z","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":"4e3a0b89d15cad7824536244e9a0ba17882f8d2692ddf8809041756477ee3291","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-02-25T12:34:24Z","title_canon_sha256":"b6baa2ee7887190963b1b4cb5d97a32fb86301cca0088f409f13025e5c79639a"},"schema_version":"1.0","source":{"id":"1902.09230","kind":"arxiv","version":1}},"canonical_sha256":"d6e9dbf47c5b8d4c41fb9879d057495e0d8156de8e7effb655468c8a5b5c1e91","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d6e9dbf47c5b8d4c41fb9879d057495e0d8156de8e7effb655468c8a5b5c1e91","first_computed_at":"2026-05-17T23:52:46.301593Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:52:46.301593Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HwL1TsAYtPwTvUaFhv2zVf5B6nX6oHaewiiAB42I50swd9VMlOcIqCBcvPTxqqN/iraTDRdWCh6s1+3oYJNkDA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:52:46.302183Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.09230","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c571a1730b067228ac30bd889bca5020442bd5a2e694f0f39c0c221a4f54da53","sha256:885ccca850654bfaea44308ee35fd37d90d481d56706f519aa0309fedd48a529"],"state_sha256":"b9bb77059babbab4dee7572bc26e3c1f2a12b8f5c2f32686f5318a3e0a8e4efc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nQL95z1bHSXE+nUCxdBsraxjP942Nv+YIUn4a+vGzSADPMKoxNZKtN92ElkIcWs6tBrQWr85AsvdoxzJbNwSDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T23:31:04.770223Z","bundle_sha256":"338248cdbf8f7bbddb7aaf691de53abf6e9f867f76892e93f543f42f31c5776e"}}