{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:IAMGG6OMI4YVV7TSME7N2ZMBAM","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":"dcd0276c980d81eee47db5f90c8b1fdc2896d1ce56a352f3cc6852002d4de475","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-01-28T14:37:22Z","title_canon_sha256":"502c5fb849415c08e677cf8155d39e26ee2c4bd81a26a961361326bd47e34a24"},"schema_version":"1.0","source":{"id":"1401.7195","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1401.7195","created_at":"2026-05-18T02:56:43Z"},{"alias_kind":"arxiv_version","alias_value":"1401.7195v1","created_at":"2026-05-18T02:56:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1401.7195","created_at":"2026-05-18T02:56:43Z"},{"alias_kind":"pith_short_12","alias_value":"IAMGG6OMI4YV","created_at":"2026-05-18T12:28:33Z"},{"alias_kind":"pith_short_16","alias_value":"IAMGG6OMI4YVV7TS","created_at":"2026-05-18T12:28:33Z"},{"alias_kind":"pith_short_8","alias_value":"IAMGG6OM","created_at":"2026-05-18T12:28:33Z"}],"graph_snapshots":[{"event_id":"sha256:7fe0c6f6db8afd6cf4bc09ac7c50d625bed78b0759c7e2f504e0be78b8a31dc1","target":"graph","created_at":"2026-05-18T02:56:43Z","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":"We derive a maximum a posteriori estimator for the linear observation model, where the signal and noise covariance matrices are both uncertain. The uncertainties are treated probabilistically by modeling the covariance matrices with prior inverse-Wishart distributions. The nonconvex problem of jointly estimating the signal of interest and the covariance matrices is tackled by a computationally efficient fixed-point iteration as well as an approximate variational Bayes solution. The statistical performance of estimators is compared numerically to state-of-the-art estimators from the literature ","authors_text":"Dave Zachariah, Magnus Jansson, Mats Bengtsson, Nafiseh Shariati, Saikat Chatterjee","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-01-28T14:37:22Z","title":"Estimation for the Linear Model with Uncertain Covariance Matrices"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1401.7195","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:c5b62b08470979ac43bd94c54ed0e8d0251595a5f9096baea5cbf6dabf95756f","target":"record","created_at":"2026-05-18T02:56:43Z","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":"dcd0276c980d81eee47db5f90c8b1fdc2896d1ce56a352f3cc6852002d4de475","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-01-28T14:37:22Z","title_canon_sha256":"502c5fb849415c08e677cf8155d39e26ee2c4bd81a26a961361326bd47e34a24"},"schema_version":"1.0","source":{"id":"1401.7195","kind":"arxiv","version":1}},"canonical_sha256":"40186379cc47315afe72613edd658103206e38066578530a7695142ed76f361c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"40186379cc47315afe72613edd658103206e38066578530a7695142ed76f361c","first_computed_at":"2026-05-18T02:56:43.533203Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:56:43.533203Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lOFc1A5Na6f3WFi0o+k/267gOhPRtXBPfvZl4SHSUt3TQf3lVLOf0KSnayp4HnImqkeLvl4u3mIBHr3En6piAw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:56:43.533667Z","signed_message":"canonical_sha256_bytes"},"source_id":"1401.7195","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c5b62b08470979ac43bd94c54ed0e8d0251595a5f9096baea5cbf6dabf95756f","sha256:7fe0c6f6db8afd6cf4bc09ac7c50d625bed78b0759c7e2f504e0be78b8a31dc1"],"state_sha256":"b75220b60f0d361fdaa9889d82ce3f598e98fd55c33728b7d8b825f0570e6248"}