{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:RS6OYLEKMHDO62Q2DXWVC274XX","short_pith_number":"pith:RS6OYLEK","canonical_record":{"source":{"id":"1906.03225","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-06-03T13:56:13Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"9ea419bb367e1678a875419e9753ae8f157683ccd43cd37e0409a0642dae70f4","abstract_canon_sha256":"cc7433cbd0bcc8c02a5934b8f3c716c1b5df104c81ff969734774c9f5e2cc486"},"schema_version":"1.0"},"canonical_sha256":"8cbcec2c8a61c6ef6a1a1ded516bfcbdd3b99006c6986d7024ae69e5c995b9bf","source":{"kind":"arxiv","id":"1906.03225","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.03225","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"arxiv_version","alias_value":"1906.03225v4","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.03225","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"pith_short_12","alias_value":"RS6OYLEKMHDO","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"pith_short_16","alias_value":"RS6OYLEKMHDO62Q2","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"pith_short_8","alias_value":"RS6OYLEK","created_at":"2026-07-05T01:22:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:RS6OYLEKMHDO62Q2DXWVC274XX","target":"record","payload":{"canonical_record":{"source":{"id":"1906.03225","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-06-03T13:56:13Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"9ea419bb367e1678a875419e9753ae8f157683ccd43cd37e0409a0642dae70f4","abstract_canon_sha256":"cc7433cbd0bcc8c02a5934b8f3c716c1b5df104c81ff969734774c9f5e2cc486"},"schema_version":"1.0"},"canonical_sha256":"8cbcec2c8a61c6ef6a1a1ded516bfcbdd3b99006c6986d7024ae69e5c995b9bf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:22:14.124549Z","signature_b64":"5f4hYeIxtq24CKkUS07LoCcbmabyEjih6nAc5Eusqswj35kQrsZzmvALmejNj9SoOL0x9dtYG9T7A52lfxEFBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8cbcec2c8a61c6ef6a1a1ded516bfcbdd3b99006c6986d7024ae69e5c995b9bf","last_reissued_at":"2026-07-05T01:22:14.124099Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:22:14.124099Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.03225","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:22:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mi0vmnNwxzCgsRDFMlvU2M8sHUdjk/csRrhJLbA8ZffIIrNTP6CxRd6Mcw+z3mlUDR2N8iH2gBItMqSCnltXBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T11:50:13.079277Z"},"content_sha256":"221a1f64194c8dc7c8b84b9e10b7c180c12195df0c516c3c8adc4af8dca717d2","schema_version":"1.0","event_id":"sha256:221a1f64194c8dc7c8b84b9e10b7c180c12195df0c516c3c8adc4af8dca717d2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:RS6OYLEKMHDO62Q2DXWVC274XX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A new approach for open-end sequential change point monitoring","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME","stat.TH"],"primary_cat":"math.ST","authors_text":"Holger Dette, Josua G\\\"osmann, Tobias Kley","submitted_at":"2019-06-03T13:56:13Z","abstract_excerpt":"We propose a new sequential monitoring scheme for changes in the parameters of a multivariate time series. In contrast to procedures proposed in the literature which compare an estimator from the training sample with an estimator calculated from the remaining data, we suggest to divide the sample at each time point after the training sample. Estimators from the sample before and after all separation points are then continuously compared calculating a maximum of norms of their differences. For open-end scenarios our approach yields an asymptotic level $\\alpha$ procedure, which is consistent und"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.03225","kind":"arxiv","version":4},"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/1906.03225/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:22:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l+VP1+fSUV88Ke3zhY7KfsLGJ7oRxS8azcaBMRjR3doUU/dCzs7WdJ5EFvRYRVHVoy3Zxr3XU3Kc4119qwsRAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T11:50:13.080657Z"},"content_sha256":"ca99c0e618477fcb4e79d2aff0cfe163073a1e0b85405aa42dc79a85f9ba1079","schema_version":"1.0","event_id":"sha256:ca99c0e618477fcb4e79d2aff0cfe163073a1e0b85405aa42dc79a85f9ba1079"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RS6OYLEKMHDO62Q2DXWVC274XX/bundle.json","state_url":"https://pith.science/pith/RS6OYLEKMHDO62Q2DXWVC274XX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RS6OYLEKMHDO62Q2DXWVC274XX/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":"2026-08-04T11:50:13Z","links":{"resolver":"https://pith.science/pith/RS6OYLEKMHDO62Q2DXWVC274XX","bundle":"https://pith.science/pith/RS6OYLEKMHDO62Q2DXWVC274XX/bundle.json","state":"https://pith.science/pith/RS6OYLEKMHDO62Q2DXWVC274XX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RS6OYLEKMHDO62Q2DXWVC274XX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:RS6OYLEKMHDO62Q2DXWVC274XX","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":"cc7433cbd0bcc8c02a5934b8f3c716c1b5df104c81ff969734774c9f5e2cc486","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-06-03T13:56:13Z","title_canon_sha256":"9ea419bb367e1678a875419e9753ae8f157683ccd43cd37e0409a0642dae70f4"},"schema_version":"1.0","source":{"id":"1906.03225","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.03225","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"arxiv_version","alias_value":"1906.03225v4","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.03225","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"pith_short_12","alias_value":"RS6OYLEKMHDO","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"pith_short_16","alias_value":"RS6OYLEKMHDO62Q2","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"pith_short_8","alias_value":"RS6OYLEK","created_at":"2026-07-05T01:22:14Z"}],"graph_snapshots":[{"event_id":"sha256:ca99c0e618477fcb4e79d2aff0cfe163073a1e0b85405aa42dc79a85f9ba1079","target":"graph","created_at":"2026-07-05T01:22:14Z","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/1906.03225/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a new sequential monitoring scheme for changes in the parameters of a multivariate time series. In contrast to procedures proposed in the literature which compare an estimator from the training sample with an estimator calculated from the remaining data, we suggest to divide the sample at each time point after the training sample. Estimators from the sample before and after all separation points are then continuously compared calculating a maximum of norms of their differences. For open-end scenarios our approach yields an asymptotic level $\\alpha$ procedure, which is consistent und","authors_text":"Holger Dette, Josua G\\\"osmann, Tobias Kley","cross_cats":["stat.ME","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-06-03T13:56:13Z","title":"A new approach for open-end sequential change point monitoring"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.03225","kind":"arxiv","version":4},"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":"sha256:221a1f64194c8dc7c8b84b9e10b7c180c12195df0c516c3c8adc4af8dca717d2","target":"record","created_at":"2026-07-05T01:22:14Z","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":"cc7433cbd0bcc8c02a5934b8f3c716c1b5df104c81ff969734774c9f5e2cc486","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-06-03T13:56:13Z","title_canon_sha256":"9ea419bb367e1678a875419e9753ae8f157683ccd43cd37e0409a0642dae70f4"},"schema_version":"1.0","source":{"id":"1906.03225","kind":"arxiv","version":4}},"canonical_sha256":"8cbcec2c8a61c6ef6a1a1ded516bfcbdd3b99006c6986d7024ae69e5c995b9bf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8cbcec2c8a61c6ef6a1a1ded516bfcbdd3b99006c6986d7024ae69e5c995b9bf","first_computed_at":"2026-07-05T01:22:14.124099Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:22:14.124099Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5f4hYeIxtq24CKkUS07LoCcbmabyEjih6nAc5Eusqswj35kQrsZzmvALmejNj9SoOL0x9dtYG9T7A52lfxEFBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:22:14.124549Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.03225","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:221a1f64194c8dc7c8b84b9e10b7c180c12195df0c516c3c8adc4af8dca717d2","sha256:ca99c0e618477fcb4e79d2aff0cfe163073a1e0b85405aa42dc79a85f9ba1079"],"state_sha256":"cc0a3728922afa9a47b154e2221a514def140dc41293bf1c5bcae8e54231532e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e1KoMNf+KePWS+3wIKkhrM/ZHvQWHRlhs7x9ghH7X1ZFC1z8s/5UiAEB3h91OeRVK4uYIhqDS3FiXIXoUufADw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T11:50:13.089292Z","bundle_sha256":"33aa3ae98621931c1d081a424520dcc1df10d4fd26a02a3da48613b4d8cb895f"}}