{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:LIBOM32V6LPJ3JJ5UMUXFCB532","short_pith_number":"pith:LIBOM32V","canonical_record":{"source":{"id":"1407.3206","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-07-11T16:11:58Z","cross_cats_sorted":["math.ST","stat.TH"],"title_canon_sha256":"b37aa16b1d661464a5bcc7e1e74139033b907316a73e367f6c776229c2d133f0","abstract_canon_sha256":"6c54e476591532a30e3c28d6c258aaf85fa5bf835dd074dae884da3c266c9dc6"},"schema_version":"1.0"},"canonical_sha256":"5a02e66f55f2de9da53da32972883ddeb05b0966ab89485533a2989f9408945a","source":{"kind":"arxiv","id":"1407.3206","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1407.3206","created_at":"2026-05-18T02:47:51Z"},{"alias_kind":"arxiv_version","alias_value":"1407.3206v1","created_at":"2026-05-18T02:47:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1407.3206","created_at":"2026-05-18T02:47:51Z"},{"alias_kind":"pith_short_12","alias_value":"LIBOM32V6LPJ","created_at":"2026-05-18T12:28:38Z"},{"alias_kind":"pith_short_16","alias_value":"LIBOM32V6LPJ3JJ5","created_at":"2026-05-18T12:28:38Z"},{"alias_kind":"pith_short_8","alias_value":"LIBOM32V","created_at":"2026-05-18T12:28:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:LIBOM32V6LPJ3JJ5UMUXFCB532","target":"record","payload":{"canonical_record":{"source":{"id":"1407.3206","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-07-11T16:11:58Z","cross_cats_sorted":["math.ST","stat.TH"],"title_canon_sha256":"b37aa16b1d661464a5bcc7e1e74139033b907316a73e367f6c776229c2d133f0","abstract_canon_sha256":"6c54e476591532a30e3c28d6c258aaf85fa5bf835dd074dae884da3c266c9dc6"},"schema_version":"1.0"},"canonical_sha256":"5a02e66f55f2de9da53da32972883ddeb05b0966ab89485533a2989f9408945a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:47:51.739451Z","signature_b64":"2JqdsqVEAF3IMychaN2iE7N22LJcBeusTQtnP1qWgWwmEiu/d75hvNCLRebeO4WMSWSljozHr78j3zReczxQCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5a02e66f55f2de9da53da32972883ddeb05b0966ab89485533a2989f9408945a","last_reissued_at":"2026-05-18T02:47:51.738953Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:47:51.738953Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1407.3206","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":"2026-05-18T02:47:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T3ylvgfMqdtpPURXBimIIrfjQz8tA9eac3+XuG6NiZAPP8OPUsm1DfVU8Gk4wmvokhWjizYjF5r4YTwQr4upDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T13:01:39.419141Z"},"content_sha256":"a07434797ab4be45c4492d1b6259d46755fe40eabbd92172d6f5897a654a1792","schema_version":"1.0","event_id":"sha256:a07434797ab4be45c4492d1b6259d46755fe40eabbd92172d6f5897a654a1792"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:LIBOM32V6LPJ3JJ5UMUXFCB532","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian Model for Multiple Change-points Detection in Multivariate Time Series","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.ST","stat.TH"],"primary_cat":"stat.ME","authors_text":"C\\'edric Gouy-Pailler, Flore Harl\\'e, Florent Chatelain, Sophie Achard","submitted_at":"2014-07-11T16:11:58Z","abstract_excerpt":"This paper addresses the issue of detecting change-points in multivariate time series. The proposed approach differs from existing counterparts by making only weak assumptions on both the change-points structure across series, and the statistical signal distributions. Specifically change-points are not assumed to occur at simultaneous time instants across series, and no specific distribution is assumed on the individual signals. It relies on the combination of a local robust statistical test acting on individual time segments, with a global Bayesian framework able to optimize configurations fr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1407.3206","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":"2026-05-18T02:47:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NPA+JYmXkZQQjFrX6V6/KoqZlKuvyGm64pvJo5o77LcqG+kHVSme+u6ZR/Tl+K3e73HKq4/ibVjy5c++drt4Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T13:01:39.419502Z"},"content_sha256":"3b9975e6ea9fee7971fe3fe4013d19b4bc70fdb63a38cde6cc03e473a74d7834","schema_version":"1.0","event_id":"sha256:3b9975e6ea9fee7971fe3fe4013d19b4bc70fdb63a38cde6cc03e473a74d7834"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LIBOM32V6LPJ3JJ5UMUXFCB532/bundle.json","state_url":"https://pith.science/pith/LIBOM32V6LPJ3JJ5UMUXFCB532/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LIBOM32V6LPJ3JJ5UMUXFCB532/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":"2026-06-06T13:01:39Z","links":{"resolver":"https://pith.science/pith/LIBOM32V6LPJ3JJ5UMUXFCB532","bundle":"https://pith.science/pith/LIBOM32V6LPJ3JJ5UMUXFCB532/bundle.json","state":"https://pith.science/pith/LIBOM32V6LPJ3JJ5UMUXFCB532/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LIBOM32V6LPJ3JJ5UMUXFCB532/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:LIBOM32V6LPJ3JJ5UMUXFCB532","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":"6c54e476591532a30e3c28d6c258aaf85fa5bf835dd074dae884da3c266c9dc6","cross_cats_sorted":["math.ST","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-07-11T16:11:58Z","title_canon_sha256":"b37aa16b1d661464a5bcc7e1e74139033b907316a73e367f6c776229c2d133f0"},"schema_version":"1.0","source":{"id":"1407.3206","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1407.3206","created_at":"2026-05-18T02:47:51Z"},{"alias_kind":"arxiv_version","alias_value":"1407.3206v1","created_at":"2026-05-18T02:47:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1407.3206","created_at":"2026-05-18T02:47:51Z"},{"alias_kind":"pith_short_12","alias_value":"LIBOM32V6LPJ","created_at":"2026-05-18T12:28:38Z"},{"alias_kind":"pith_short_16","alias_value":"LIBOM32V6LPJ3JJ5","created_at":"2026-05-18T12:28:38Z"},{"alias_kind":"pith_short_8","alias_value":"LIBOM32V","created_at":"2026-05-18T12:28:38Z"}],"graph_snapshots":[{"event_id":"sha256:3b9975e6ea9fee7971fe3fe4013d19b4bc70fdb63a38cde6cc03e473a74d7834","target":"graph","created_at":"2026-05-18T02:47:51Z","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":"This paper addresses the issue of detecting change-points in multivariate time series. The proposed approach differs from existing counterparts by making only weak assumptions on both the change-points structure across series, and the statistical signal distributions. Specifically change-points are not assumed to occur at simultaneous time instants across series, and no specific distribution is assumed on the individual signals. It relies on the combination of a local robust statistical test acting on individual time segments, with a global Bayesian framework able to optimize configurations fr","authors_text":"C\\'edric Gouy-Pailler, Flore Harl\\'e, Florent Chatelain, Sophie Achard","cross_cats":["math.ST","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-07-11T16:11:58Z","title":"Bayesian Model for Multiple Change-points Detection in Multivariate Time Series"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1407.3206","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:a07434797ab4be45c4492d1b6259d46755fe40eabbd92172d6f5897a654a1792","target":"record","created_at":"2026-05-18T02:47:51Z","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":"6c54e476591532a30e3c28d6c258aaf85fa5bf835dd074dae884da3c266c9dc6","cross_cats_sorted":["math.ST","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-07-11T16:11:58Z","title_canon_sha256":"b37aa16b1d661464a5bcc7e1e74139033b907316a73e367f6c776229c2d133f0"},"schema_version":"1.0","source":{"id":"1407.3206","kind":"arxiv","version":1}},"canonical_sha256":"5a02e66f55f2de9da53da32972883ddeb05b0966ab89485533a2989f9408945a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5a02e66f55f2de9da53da32972883ddeb05b0966ab89485533a2989f9408945a","first_computed_at":"2026-05-18T02:47:51.738953Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:47:51.738953Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2JqdsqVEAF3IMychaN2iE7N22LJcBeusTQtnP1qWgWwmEiu/d75hvNCLRebeO4WMSWSljozHr78j3zReczxQCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T02:47:51.739451Z","signed_message":"canonical_sha256_bytes"},"source_id":"1407.3206","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a07434797ab4be45c4492d1b6259d46755fe40eabbd92172d6f5897a654a1792","sha256:3b9975e6ea9fee7971fe3fe4013d19b4bc70fdb63a38cde6cc03e473a74d7834"],"state_sha256":"0bbaa7c9fdff4545df049373c0c497484335237452a9c05700690c2962c21441"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BsNsOGzcvpXErxHrDvAifSlfl3xFW/pzx5i7WYuSVU+Uz+uo/dYuP3w9BfhAltD8CoCpbJfX/oovuM3uL0ibDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T13:01:39.421373Z","bundle_sha256":"6378bc01237301a68ed2ad33595f82dcf9c5d3d8a25e6046bb0dc4fd3ceb93fe"}}