{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:XBLMSFMSG2L2UA7KHIRKSAGATT","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":"4fe60b3d0a36587d7ebcf778e996bb3745cd1eb11e25f83546226e230fcb8f75","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-10-25T01:07:43Z","title_canon_sha256":"a8712864fcab6049b6b8c46daacaa0f3fe10cc23d6130ce5aa794e6408414bc3"},"schema_version":"1.0","source":{"id":"1610.07697","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1610.07697","created_at":"2026-05-18T01:01:21Z"},{"alias_kind":"arxiv_version","alias_value":"1610.07697v1","created_at":"2026-05-18T01:01:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.07697","created_at":"2026-05-18T01:01:21Z"},{"alias_kind":"pith_short_12","alias_value":"XBLMSFMSG2L2","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_16","alias_value":"XBLMSFMSG2L2UA7K","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_8","alias_value":"XBLMSFMS","created_at":"2026-05-18T12:30:51Z"}],"graph_snapshots":[{"event_id":"sha256:5236d62e46aa08a96881abf66942b6a3c21545c4ce475289b5bac2823ac88004","target":"graph","created_at":"2026-05-18T01:01:21Z","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":"Factor modeling is an essential tool for exploring intrinsic dependence structures among high-dimensional random variables. Much progress has been made for estimating the covariance matrix from a high-dimensional factor model. However, the blessing of dimensionality has not yet been fully embraced in the literature: much of the available data is often ignored in constructing covariance matrix estimates. If our goal is to accurately estimate a covariance matrix of a set of targeted variables, shall we employ additional data, which are beyond the variables of interest, in the estimation? In this","authors_text":"Guang Cheng, Jianqing Fan, Quefeng Li, Yuyan Wang","cross_cats":["stat.ME","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-10-25T01:07:43Z","title":"Embracing the Blessing of Dimensionality in Factor Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.07697","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":"sha256:1f62ca72dc5c9e14e281f0bd3d284393e8d19eeb2b73967062a5bf9b7eb32c2c","target":"record","created_at":"2026-05-18T01:01:21Z","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":"4fe60b3d0a36587d7ebcf778e996bb3745cd1eb11e25f83546226e230fcb8f75","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-10-25T01:07:43Z","title_canon_sha256":"a8712864fcab6049b6b8c46daacaa0f3fe10cc23d6130ce5aa794e6408414bc3"},"schema_version":"1.0","source":{"id":"1610.07697","kind":"arxiv","version":1}},"canonical_sha256":"b856c915923697aa03ea3a22a900c09cd2b99dfd96fd6a43618ffaa1e4a6d05b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b856c915923697aa03ea3a22a900c09cd2b99dfd96fd6a43618ffaa1e4a6d05b","first_computed_at":"2026-05-18T01:01:21.464630Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:01:21.464630Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+EE7y9Qkdfo76EVkwlnWRnzLCCiTMGQSHRDslMVKLwT3YKLFgVZyoQ+CUWBXDb+g9GF1IZsp0wrfJyGskrG1BQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:01:21.465163Z","signed_message":"canonical_sha256_bytes"},"source_id":"1610.07697","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1f62ca72dc5c9e14e281f0bd3d284393e8d19eeb2b73967062a5bf9b7eb32c2c","sha256:5236d62e46aa08a96881abf66942b6a3c21545c4ce475289b5bac2823ac88004"],"state_sha256":"9008aa13de37ac42537e69076195bdb535d6d78ab0080777cc6e3c3d01ca71e7"}