{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:ZHLVRE7TQPTCCV3NNULSWUXRF4","short_pith_number":"pith:ZHLVRE7T","schema_version":"1.0","canonical_sha256":"c9d75893f383e621576d6d172b52f12f0ba832bd141b354479550bb42420afd5","source":{"kind":"arxiv","id":"1607.04751","version":2},"attestation_state":"computed","paper":{"title":"Fast Simulation of Hyperplane-Truncated Multivariate Normal Distributions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"Bo Chen, Mingyuan Zhou, Yulai Cong","submitted_at":"2016-07-16T15:36:04Z","abstract_excerpt":"We introduce a fast and easy-to-implement simulation algorithm for a multivariate normal distribution truncated on the intersection of a set of hyperplanes, and further generalize it to efficiently simulate random variables from a multivariate normal distribution whose covariance (precision) matrix can be decomposed as a positive-definite matrix minus (plus) a low-rank symmetric matrix. Example results illustrate the correctness and efficiency of the proposed simulation algorithms."},"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":"1607.04751","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2016-07-16T15:36:04Z","cross_cats_sorted":[],"title_canon_sha256":"bde53311f164d33f181f1ea1659749d6cbbbcccfd0074f7a0d6e72dd6e6b225f","abstract_canon_sha256":"d91d24f7bf26d7f579c7ad00c0257d4fc8f6c2643014fb4a2ec81512afb74e66"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:50:31.021110Z","signature_b64":"cHuTzFHfN5z7Pw9lDbMYOsAXJMPw5fSfLAD4jCV0/8LpuExCDTIwLW+fgIhlfth7X7tQkzwAQ7qMT/WRdj8rDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c9d75893f383e621576d6d172b52f12f0ba832bd141b354479550bb42420afd5","last_reissued_at":"2026-05-18T00:50:31.020490Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:50:31.020490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fast Simulation of Hyperplane-Truncated Multivariate Normal Distributions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"Bo Chen, Mingyuan Zhou, Yulai Cong","submitted_at":"2016-07-16T15:36:04Z","abstract_excerpt":"We introduce a fast and easy-to-implement simulation algorithm for a multivariate normal distribution truncated on the intersection of a set of hyperplanes, and further generalize it to efficiently simulate random variables from a multivariate normal distribution whose covariance (precision) matrix can be decomposed as a positive-definite matrix minus (plus) a low-rank symmetric matrix. Example results illustrate the correctness and efficiency of the proposed simulation algorithms."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.04751","kind":"arxiv","version":2},"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":"1607.04751","created_at":"2026-05-18T00:50:31.020601+00:00"},{"alias_kind":"arxiv_version","alias_value":"1607.04751v2","created_at":"2026-05-18T00:50:31.020601+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.04751","created_at":"2026-05-18T00:50:31.020601+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZHLVRE7TQPTC","created_at":"2026-05-18T12:30:53.716459+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZHLVRE7TQPTCCV3N","created_at":"2026-05-18T12:30:53.716459+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZHLVRE7T","created_at":"2026-05-18T12:30:53.716459+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/ZHLVRE7TQPTCCV3NNULSWUXRF4","json":"https://pith.science/pith/ZHLVRE7TQPTCCV3NNULSWUXRF4.json","graph_json":"https://pith.science/api/pith-number/ZHLVRE7TQPTCCV3NNULSWUXRF4/graph.json","events_json":"https://pith.science/api/pith-number/ZHLVRE7TQPTCCV3NNULSWUXRF4/events.json","paper":"https://pith.science/paper/ZHLVRE7T"},"agent_actions":{"view_html":"https://pith.science/pith/ZHLVRE7TQPTCCV3NNULSWUXRF4","download_json":"https://pith.science/pith/ZHLVRE7TQPTCCV3NNULSWUXRF4.json","view_paper":"https://pith.science/paper/ZHLVRE7T","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1607.04751&json=true","fetch_graph":"https://pith.science/api/pith-number/ZHLVRE7TQPTCCV3NNULSWUXRF4/graph.json","fetch_events":"https://pith.science/api/pith-number/ZHLVRE7TQPTCCV3NNULSWUXRF4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZHLVRE7TQPTCCV3NNULSWUXRF4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZHLVRE7TQPTCCV3NNULSWUXRF4/action/storage_attestation","attest_author":"https://pith.science/pith/ZHLVRE7TQPTCCV3NNULSWUXRF4/action/author_attestation","sign_citation":"https://pith.science/pith/ZHLVRE7TQPTCCV3NNULSWUXRF4/action/citation_signature","submit_replication":"https://pith.science/pith/ZHLVRE7TQPTCCV3NNULSWUXRF4/action/replication_record"}},"created_at":"2026-05-18T00:50:31.020601+00:00","updated_at":"2026-05-18T00:50:31.020601+00:00"}