{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:KGOI3TR2DAENCNRT3ZG6C2HNJQ","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":"0fa1c4b336335b09d8a3964b6b53ff45facd1608dfbb02a36418a16edbee206d","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-10-26T16:24:41Z","title_canon_sha256":"539b3c39c1a090dcf2934fb16b6a0be8021cacfc19a81be5cd160673b47059e4"},"schema_version":"1.0","source":{"id":"1410.7056","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1410.7056","created_at":"2026-05-18T02:39:18Z"},{"alias_kind":"arxiv_version","alias_value":"1410.7056v1","created_at":"2026-05-18T02:39:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1410.7056","created_at":"2026-05-18T02:39:18Z"},{"alias_kind":"pith_short_12","alias_value":"KGOI3TR2DAEN","created_at":"2026-05-18T12:28:35Z"},{"alias_kind":"pith_short_16","alias_value":"KGOI3TR2DAENCNRT","created_at":"2026-05-18T12:28:35Z"},{"alias_kind":"pith_short_8","alias_value":"KGOI3TR2","created_at":"2026-05-18T12:28:35Z"}],"graph_snapshots":[{"event_id":"sha256:61376a1b931e90e01fee7718a353c56f0642592ab2f685eb6bc8befaf1963c49","target":"graph","created_at":"2026-05-18T02:39:18Z","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 develop constrained Bayesian estimation methods for small area problems: those requiring smoothness with respect to similarity across areas, such as geographic proximity or clustering by covariates; and benchmarking constraints, requiring (weighted) means of estimates to agree across levels of aggregation. We develop methods for constrained estimation decision-theoretically and discuss their geometric interpretation. Our constrained estimators are the solutions to tractable optimization problems and have closed-form solutions. Mean squared errors of the constrained estimators are calculated","authors_text":"Rebecca C. Steorts","cross_cats":["stat.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-10-26T16:24:41Z","title":"Smoothing, Clustering, and Benchmarking for Small Area Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1410.7056","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:b81e6a399c48ba2c2db0756ef6f9089afc3e92bd9aab3bbc7d443b3fd6eb7a26","target":"record","created_at":"2026-05-18T02:39:18Z","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":"0fa1c4b336335b09d8a3964b6b53ff45facd1608dfbb02a36418a16edbee206d","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-10-26T16:24:41Z","title_canon_sha256":"539b3c39c1a090dcf2934fb16b6a0be8021cacfc19a81be5cd160673b47059e4"},"schema_version":"1.0","source":{"id":"1410.7056","kind":"arxiv","version":1}},"canonical_sha256":"519c8dce3a1808d13633de4de168ed4c1752ee79dd56c03348316751a0e57972","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"519c8dce3a1808d13633de4de168ed4c1752ee79dd56c03348316751a0e57972","first_computed_at":"2026-05-18T02:39:18.081971Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:39:18.081971Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"X7CspPBRxe+UZJKMVMjX3IrlK1Tqkg64IGq0WiN99LCwDxRsMK0fyj+I3TifcM5yTizb1jdW/fA7dqI08HkrBw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:39:18.082442Z","signed_message":"canonical_sha256_bytes"},"source_id":"1410.7056","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b81e6a399c48ba2c2db0756ef6f9089afc3e92bd9aab3bbc7d443b3fd6eb7a26","sha256:61376a1b931e90e01fee7718a353c56f0642592ab2f685eb6bc8befaf1963c49"],"state_sha256":"c8f1427769071f85f2505252e3a4933b8a96a0b3bc50a52693c37d70e56a0903"}