{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:ACYFMPGPA2CYIHXREHUCYKUVXW","short_pith_number":"pith:ACYFMPGP","canonical_record":{"source":{"id":"1307.2662","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2013-07-10T03:38:26Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"57ed7dabbbe513915b2842ed5c56a2ad5291a55ca9b1d164a9c34e4f3c6a4d2f","abstract_canon_sha256":"3173d4df332542807843a2de4c152c24d2aa3eefab50077a94cc4612b22b9f46"},"schema_version":"1.0"},"canonical_sha256":"00b0563ccf0685841ef121e82c2a95bda43166efae34e74d9aa7f9e69e994b9e","source":{"kind":"arxiv","id":"1307.2662","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1307.2662","created_at":"2026-05-18T03:07:23Z"},{"alias_kind":"arxiv_version","alias_value":"1307.2662v4","created_at":"2026-05-18T03:07:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1307.2662","created_at":"2026-05-18T03:07:23Z"},{"alias_kind":"pith_short_12","alias_value":"ACYFMPGPA2CY","created_at":"2026-05-18T12:27:38Z"},{"alias_kind":"pith_short_16","alias_value":"ACYFMPGPA2CYIHXR","created_at":"2026-05-18T12:27:38Z"},{"alias_kind":"pith_short_8","alias_value":"ACYFMPGP","created_at":"2026-05-18T12:27:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:ACYFMPGPA2CYIHXREHUCYKUVXW","target":"record","payload":{"canonical_record":{"source":{"id":"1307.2662","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2013-07-10T03:38:26Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"57ed7dabbbe513915b2842ed5c56a2ad5291a55ca9b1d164a9c34e4f3c6a4d2f","abstract_canon_sha256":"3173d4df332542807843a2de4c152c24d2aa3eefab50077a94cc4612b22b9f46"},"schema_version":"1.0"},"canonical_sha256":"00b0563ccf0685841ef121e82c2a95bda43166efae34e74d9aa7f9e69e994b9e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:07:23.146302Z","signature_b64":"xuLYITNx9137R+KiL8+UFQHpG9LQEi9OGYnNXeMFCSU+q0xx6s7IpnIiM6E5sy8Jg3+rnIyXXtZRae4ZwgXKAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"00b0563ccf0685841ef121e82c2a95bda43166efae34e74d9aa7f9e69e994b9e","last_reissued_at":"2026-05-18T03:07:23.145439Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:07:23.145439Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1307.2662","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":"2026-05-18T03:07:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ycpSjyduf1JjvwxuqCvd1vIRgEJObNQBrXdzLct9yLSrnx6dLe0Dt/Sw3SMZ9Ql8TbpK+GXmRl4Kc8UtMH+MDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T03:24:26.401651Z"},"content_sha256":"9fb6080ecf43fb448c1c7cbb868b0551a8155936d210fbd9b2b8303b3e0cb8b8","schema_version":"1.0","event_id":"sha256:9fb6080ecf43fb448c1c7cbb868b0551a8155936d210fbd9b2b8303b3e0cb8b8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:ACYFMPGPA2CYIHXREHUCYKUVXW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Statistical Inferences Using Large Estimated Covariances for Panel Data and Factor Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Jushan Bai, Yuan Liao","submitted_at":"2013-07-10T03:38:26Z","abstract_excerpt":"While most of the convergence results in the literature on high dimensional covariance matrix are concerned about the accuracy of estimating the covariance matrix (and precision matrix), relatively less is known about the effect of estimating large covariances on statistical inferences. We study two important models: factor analysis and panel data model with interactive effects, and focus on the statistical inference and estimation efficiency of structural parameters based on large covariance estimators. For efficient estimation, both models call for a weighted principle components (WPC), whic"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1307.2662","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":""},"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":"2026-05-18T03:07:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KRYNC7+f6C7Ygk/BraHgR5LlP/w1x307YyhWN43S5I9yZ58roaFZ+SotgY0bNysV7YzWuGo47fZ7c8wkAoSNBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T03:24:26.402259Z"},"content_sha256":"196508d88fbd0a354e327a9ab4ce14f5b73d34bf54bb03315a914c28dbe4f744","schema_version":"1.0","event_id":"sha256:196508d88fbd0a354e327a9ab4ce14f5b73d34bf54bb03315a914c28dbe4f744"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ACYFMPGPA2CYIHXREHUCYKUVXW/bundle.json","state_url":"https://pith.science/pith/ACYFMPGPA2CYIHXREHUCYKUVXW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ACYFMPGPA2CYIHXREHUCYKUVXW/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":"2026-06-09T03:24:26Z","links":{"resolver":"https://pith.science/pith/ACYFMPGPA2CYIHXREHUCYKUVXW","bundle":"https://pith.science/pith/ACYFMPGPA2CYIHXREHUCYKUVXW/bundle.json","state":"https://pith.science/pith/ACYFMPGPA2CYIHXREHUCYKUVXW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ACYFMPGPA2CYIHXREHUCYKUVXW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:ACYFMPGPA2CYIHXREHUCYKUVXW","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":"3173d4df332542807843a2de4c152c24d2aa3eefab50077a94cc4612b22b9f46","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2013-07-10T03:38:26Z","title_canon_sha256":"57ed7dabbbe513915b2842ed5c56a2ad5291a55ca9b1d164a9c34e4f3c6a4d2f"},"schema_version":"1.0","source":{"id":"1307.2662","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1307.2662","created_at":"2026-05-18T03:07:23Z"},{"alias_kind":"arxiv_version","alias_value":"1307.2662v4","created_at":"2026-05-18T03:07:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1307.2662","created_at":"2026-05-18T03:07:23Z"},{"alias_kind":"pith_short_12","alias_value":"ACYFMPGPA2CY","created_at":"2026-05-18T12:27:38Z"},{"alias_kind":"pith_short_16","alias_value":"ACYFMPGPA2CYIHXR","created_at":"2026-05-18T12:27:38Z"},{"alias_kind":"pith_short_8","alias_value":"ACYFMPGP","created_at":"2026-05-18T12:27:38Z"}],"graph_snapshots":[{"event_id":"sha256:196508d88fbd0a354e327a9ab4ce14f5b73d34bf54bb03315a914c28dbe4f744","target":"graph","created_at":"2026-05-18T03:07:23Z","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":"While most of the convergence results in the literature on high dimensional covariance matrix are concerned about the accuracy of estimating the covariance matrix (and precision matrix), relatively less is known about the effect of estimating large covariances on statistical inferences. We study two important models: factor analysis and panel data model with interactive effects, and focus on the statistical inference and estimation efficiency of structural parameters based on large covariance estimators. For efficient estimation, both models call for a weighted principle components (WPC), whic","authors_text":"Jushan Bai, Yuan Liao","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2013-07-10T03:38:26Z","title":"Statistical Inferences Using Large Estimated Covariances for Panel Data and Factor Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1307.2662","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":"sha256:9fb6080ecf43fb448c1c7cbb868b0551a8155936d210fbd9b2b8303b3e0cb8b8","target":"record","created_at":"2026-05-18T03:07:23Z","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":"3173d4df332542807843a2de4c152c24d2aa3eefab50077a94cc4612b22b9f46","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2013-07-10T03:38:26Z","title_canon_sha256":"57ed7dabbbe513915b2842ed5c56a2ad5291a55ca9b1d164a9c34e4f3c6a4d2f"},"schema_version":"1.0","source":{"id":"1307.2662","kind":"arxiv","version":4}},"canonical_sha256":"00b0563ccf0685841ef121e82c2a95bda43166efae34e74d9aa7f9e69e994b9e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"00b0563ccf0685841ef121e82c2a95bda43166efae34e74d9aa7f9e69e994b9e","first_computed_at":"2026-05-18T03:07:23.145439Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:07:23.145439Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xuLYITNx9137R+KiL8+UFQHpG9LQEi9OGYnNXeMFCSU+q0xx6s7IpnIiM6E5sy8Jg3+rnIyXXtZRae4ZwgXKAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T03:07:23.146302Z","signed_message":"canonical_sha256_bytes"},"source_id":"1307.2662","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9fb6080ecf43fb448c1c7cbb868b0551a8155936d210fbd9b2b8303b3e0cb8b8","sha256:196508d88fbd0a354e327a9ab4ce14f5b73d34bf54bb03315a914c28dbe4f744"],"state_sha256":"6d85a49f6a4c7d72c4e2ed1cc2d68b85bd79d8a73782b09f559835684ae97b7a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4mtCijOn2qxc3dsHbJczJF5o4lY99OOqCUnQpCj0tmNmIrFzhLGb61eOsnIRxiWWK9lCrrZfbkdukxrMM7NnCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T03:24:26.406195Z","bundle_sha256":"6a088a66f6fc015c78bf1b750b5593215e64d9c9c21321c214ee8b75d7c177e8"}}