{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:AU2HIHNTGDQMQUXY6DKKIO4XIC","short_pith_number":"pith:AU2HIHNT","canonical_record":{"source":{"id":"1610.01889","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-10-06T14:36:31Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"972a605f585391e0e1f4cf80a31d7cd99544b068208ec4bbdab0a51150473406","abstract_canon_sha256":"22f19a8c1e0432ca07f00e70d3be2dfc194cab4e49e4ec68d89b97fa9ee45fb1"},"schema_version":"1.0"},"canonical_sha256":"0534741db330e0c852f8f0d4a43b9740b8fe8b8586917126eb627943e9354a59","source":{"kind":"arxiv","id":"1610.01889","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1610.01889","created_at":"2026-05-18T00:41:58Z"},{"alias_kind":"arxiv_version","alias_value":"1610.01889v2","created_at":"2026-05-18T00:41:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.01889","created_at":"2026-05-18T00:41:58Z"},{"alias_kind":"pith_short_12","alias_value":"AU2HIHNTGDQM","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_16","alias_value":"AU2HIHNTGDQMQUXY","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_8","alias_value":"AU2HIHNT","created_at":"2026-05-18T12:30:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:AU2HIHNTGDQMQUXY6DKKIO4XIC","target":"record","payload":{"canonical_record":{"source":{"id":"1610.01889","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-10-06T14:36:31Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"972a605f585391e0e1f4cf80a31d7cd99544b068208ec4bbdab0a51150473406","abstract_canon_sha256":"22f19a8c1e0432ca07f00e70d3be2dfc194cab4e49e4ec68d89b97fa9ee45fb1"},"schema_version":"1.0"},"canonical_sha256":"0534741db330e0c852f8f0d4a43b9740b8fe8b8586917126eb627943e9354a59","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:41:58.219742Z","signature_b64":"qPrSyeB4fYHgAo1C39e1+7/emlNx8JTFMUJ7Cly+7fdmy/uO2Nj61cCbQlRyF8Ar0b1tVQV71v3WVD/C6ZvgBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0534741db330e0c852f8f0d4a43b9740b8fe8b8586917126eb627943e9354a59","last_reissued_at":"2026-05-18T00:41:58.219266Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:41:58.219266Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1610.01889","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:41:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w5x3q/d3SP6fw2XGpQ7C7UDR+smIcX440zjpWlZqVGXwD4rr8ZNS4Tx+KRVIi35AN1Ir0Zr/qZ/pI37GQJHsCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T00:13:28.360146Z"},"content_sha256":"1bf2ee2505170eeb917f043d43caf44882d80b935679e6207faf0b742884ea2c","schema_version":"1.0","event_id":"sha256:1bf2ee2505170eeb917f043d43caf44882d80b935679e6207faf0b742884ea2c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:AU2HIHNTGDQMQUXY6DKKIO4XIC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Factor Models for Matrix-Valued High-Dimensional Time Series","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"Dong Wang, Rong chen, Xialu Liu","submitted_at":"2016-10-06T14:36:31Z","abstract_excerpt":"In finance, economics and many other fields, observations in a matrix form are often observed over time. For example, many economic indicators are obtained in different countries over time. Various financial characteristics of many companies are reported over time. Although it is natural to turn a matrix observation into a long vector then use standard vector time series models or factor analysis, it is often the case that the columns and rows of a matrix represent different sets of information that are closely interrelated in a very structural way. We propose a novel factor model that maintai"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.01889","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:41:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VbuPSgHC9PrU71pxFDDlFMVsJu0pj7L3CfzldyVuKuPKyEJKAx5OGFtUnJqK3x27TiQhSDWCQ43VXk7gcEu4BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T00:13:28.360852Z"},"content_sha256":"5e451b7798604ee55bd7565c53b3e38ac5cf1d8112edb540546cf4419fe5c6cd","schema_version":"1.0","event_id":"sha256:5e451b7798604ee55bd7565c53b3e38ac5cf1d8112edb540546cf4419fe5c6cd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AU2HIHNTGDQMQUXY6DKKIO4XIC/bundle.json","state_url":"https://pith.science/pith/AU2HIHNTGDQMQUXY6DKKIO4XIC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AU2HIHNTGDQMQUXY6DKKIO4XIC/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":"2026-05-30T00:13:28Z","links":{"resolver":"https://pith.science/pith/AU2HIHNTGDQMQUXY6DKKIO4XIC","bundle":"https://pith.science/pith/AU2HIHNTGDQMQUXY6DKKIO4XIC/bundle.json","state":"https://pith.science/pith/AU2HIHNTGDQMQUXY6DKKIO4XIC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AU2HIHNTGDQMQUXY6DKKIO4XIC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:AU2HIHNTGDQMQUXY6DKKIO4XIC","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":"22f19a8c1e0432ca07f00e70d3be2dfc194cab4e49e4ec68d89b97fa9ee45fb1","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-10-06T14:36:31Z","title_canon_sha256":"972a605f585391e0e1f4cf80a31d7cd99544b068208ec4bbdab0a51150473406"},"schema_version":"1.0","source":{"id":"1610.01889","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1610.01889","created_at":"2026-05-18T00:41:58Z"},{"alias_kind":"arxiv_version","alias_value":"1610.01889v2","created_at":"2026-05-18T00:41:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.01889","created_at":"2026-05-18T00:41:58Z"},{"alias_kind":"pith_short_12","alias_value":"AU2HIHNTGDQM","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_16","alias_value":"AU2HIHNTGDQMQUXY","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_8","alias_value":"AU2HIHNT","created_at":"2026-05-18T12:30:07Z"}],"graph_snapshots":[{"event_id":"sha256:5e451b7798604ee55bd7565c53b3e38ac5cf1d8112edb540546cf4419fe5c6cd","target":"graph","created_at":"2026-05-18T00:41:58Z","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":"In finance, economics and many other fields, observations in a matrix form are often observed over time. For example, many economic indicators are obtained in different countries over time. Various financial characteristics of many companies are reported over time. Although it is natural to turn a matrix observation into a long vector then use standard vector time series models or factor analysis, it is often the case that the columns and rows of a matrix represent different sets of information that are closely interrelated in a very structural way. We propose a novel factor model that maintai","authors_text":"Dong Wang, Rong chen, Xialu Liu","cross_cats":["stat.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-10-06T14:36:31Z","title":"Factor Models for Matrix-Valued High-Dimensional Time Series"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.01889","kind":"arxiv","version":2},"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":"sha256:1bf2ee2505170eeb917f043d43caf44882d80b935679e6207faf0b742884ea2c","target":"record","created_at":"2026-05-18T00:41:58Z","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":"22f19a8c1e0432ca07f00e70d3be2dfc194cab4e49e4ec68d89b97fa9ee45fb1","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-10-06T14:36:31Z","title_canon_sha256":"972a605f585391e0e1f4cf80a31d7cd99544b068208ec4bbdab0a51150473406"},"schema_version":"1.0","source":{"id":"1610.01889","kind":"arxiv","version":2}},"canonical_sha256":"0534741db330e0c852f8f0d4a43b9740b8fe8b8586917126eb627943e9354a59","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0534741db330e0c852f8f0d4a43b9740b8fe8b8586917126eb627943e9354a59","first_computed_at":"2026-05-18T00:41:58.219266Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:41:58.219266Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qPrSyeB4fYHgAo1C39e1+7/emlNx8JTFMUJ7Cly+7fdmy/uO2Nj61cCbQlRyF8Ar0b1tVQV71v3WVD/C6ZvgBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:41:58.219742Z","signed_message":"canonical_sha256_bytes"},"source_id":"1610.01889","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1bf2ee2505170eeb917f043d43caf44882d80b935679e6207faf0b742884ea2c","sha256:5e451b7798604ee55bd7565c53b3e38ac5cf1d8112edb540546cf4419fe5c6cd"],"state_sha256":"9c86e61424dfd649a534c00b56c1646ace70144a0ce5b91c3ce946ad1387949c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P4DeV4vVTmc7lFtoAzGp8jpHz3H8KNI3WDcWSBIXikx2DJC6nJfLgEKfsOAMxrgfdTM0miciJ4zj2fOlzWF3Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T00:13:28.364710Z","bundle_sha256":"1bba3f4d6afc362a086101025c0e464feaea3e4b30e8ec3ffef75523a1a0245a"}}