{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:RL6H4ARQHEBAHI7Y3GAZJUQJD7","short_pith_number":"pith:RL6H4ARQ","schema_version":"1.0","canonical_sha256":"8afc7e0230390203a3f8d98194d2091fe8487700a3895f5916d11a0f2b1e9a62","source":{"kind":"arxiv","id":"1807.10797","version":1},"attestation_state":"computed","paper":{"title":"Estimating a change point in a sequence of very high-dimensional covariance matrices","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.ST","stat.TH"],"primary_cat":"stat.ME","authors_text":"G. M. Pan, H. Dette, Q. Yang","submitted_at":"2018-07-27T18:56:10Z","abstract_excerpt":"This paper considers the problem of estimating a change point in the covariance matrix in a sequence of high-dimensional vectors, where the dimension is substantially larger than the sample size. A two-stage approach is proposed to efficiently estimate the location of the change point. The first step consists of a reduction of the dimension to identify elements of the covariance matrices corresponding to significant changes. In a second step we use the components after dimension reduction to determine the position of the change point. Theoretical properties are developed for both steps and num"},"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":"1807.10797","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-07-27T18:56:10Z","cross_cats_sorted":["math.ST","stat.TH"],"title_canon_sha256":"da6890adffb37c9e353d57d3cbe76208d3ca1a5a105101d66c85e3a61eed451c","abstract_canon_sha256":"35aefee37c558203948e11c0b44410dbf9ff8caa27c74d853dde665b4ef95169"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:09:37.374698Z","signature_b64":"85Q/hdKMPJG4ynQXruXZp3G8fD919+NQ6b8bkec5vHUlf9T/JBMxJOuU9Fdv47DVs+jLrq2cLMedMRzYYh5ICw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8afc7e0230390203a3f8d98194d2091fe8487700a3895f5916d11a0f2b1e9a62","last_reissued_at":"2026-05-18T00:09:37.374045Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:09:37.374045Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Estimating a change point in a sequence of very high-dimensional covariance matrices","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.ST","stat.TH"],"primary_cat":"stat.ME","authors_text":"G. M. Pan, H. Dette, Q. Yang","submitted_at":"2018-07-27T18:56:10Z","abstract_excerpt":"This paper considers the problem of estimating a change point in the covariance matrix in a sequence of high-dimensional vectors, where the dimension is substantially larger than the sample size. A two-stage approach is proposed to efficiently estimate the location of the change point. The first step consists of a reduction of the dimension to identify elements of the covariance matrices corresponding to significant changes. In a second step we use the components after dimension reduction to determine the position of the change point. Theoretical properties are developed for both steps and num"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.10797","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1807.10797","created_at":"2026-05-18T00:09:37.374102+00:00"},{"alias_kind":"arxiv_version","alias_value":"1807.10797v1","created_at":"2026-05-18T00:09:37.374102+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.10797","created_at":"2026-05-18T00:09:37.374102+00:00"},{"alias_kind":"pith_short_12","alias_value":"RL6H4ARQHEBA","created_at":"2026-05-18T12:32:50.500415+00:00"},{"alias_kind":"pith_short_16","alias_value":"RL6H4ARQHEBAHI7Y","created_at":"2026-05-18T12:32:50.500415+00:00"},{"alias_kind":"pith_short_8","alias_value":"RL6H4ARQ","created_at":"2026-05-18T12:32:50.500415+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RL6H4ARQHEBAHI7Y3GAZJUQJD7","json":"https://pith.science/pith/RL6H4ARQHEBAHI7Y3GAZJUQJD7.json","graph_json":"https://pith.science/api/pith-number/RL6H4ARQHEBAHI7Y3GAZJUQJD7/graph.json","events_json":"https://pith.science/api/pith-number/RL6H4ARQHEBAHI7Y3GAZJUQJD7/events.json","paper":"https://pith.science/paper/RL6H4ARQ"},"agent_actions":{"view_html":"https://pith.science/pith/RL6H4ARQHEBAHI7Y3GAZJUQJD7","download_json":"https://pith.science/pith/RL6H4ARQHEBAHI7Y3GAZJUQJD7.json","view_paper":"https://pith.science/paper/RL6H4ARQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1807.10797&json=true","fetch_graph":"https://pith.science/api/pith-number/RL6H4ARQHEBAHI7Y3GAZJUQJD7/graph.json","fetch_events":"https://pith.science/api/pith-number/RL6H4ARQHEBAHI7Y3GAZJUQJD7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RL6H4ARQHEBAHI7Y3GAZJUQJD7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RL6H4ARQHEBAHI7Y3GAZJUQJD7/action/storage_attestation","attest_author":"https://pith.science/pith/RL6H4ARQHEBAHI7Y3GAZJUQJD7/action/author_attestation","sign_citation":"https://pith.science/pith/RL6H4ARQHEBAHI7Y3GAZJUQJD7/action/citation_signature","submit_replication":"https://pith.science/pith/RL6H4ARQHEBAHI7Y3GAZJUQJD7/action/replication_record"}},"created_at":"2026-05-18T00:09:37.374102+00:00","updated_at":"2026-05-18T00:09:37.374102+00:00"}