{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:YN26CLMPQDMMMZ23MP7MOQQ5CM","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":"91b41d137fbccb57df210142f5ccbdc2f57a74f7f28c195f7ee1517eb451d9dc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-05-25T17:49:12Z","title_canon_sha256":"13039c4999becb4cb1a3e28588b2bb30e718c45a3af093036a28eee1b589ebc8"},"schema_version":"1.0","source":{"id":"1605.07981","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1605.07981","created_at":"2026-05-18T01:13:38Z"},{"alias_kind":"arxiv_version","alias_value":"1605.07981v1","created_at":"2026-05-18T01:13:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.07981","created_at":"2026-05-18T01:13:38Z"},{"alias_kind":"pith_short_12","alias_value":"YN26CLMPQDMM","created_at":"2026-05-18T12:30:53Z"},{"alias_kind":"pith_short_16","alias_value":"YN26CLMPQDMMMZ23","created_at":"2026-05-18T12:30:53Z"},{"alias_kind":"pith_short_8","alias_value":"YN26CLMP","created_at":"2026-05-18T12:30:53Z"}],"graph_snapshots":[{"event_id":"sha256:ef77bd330c790f45eaa2459d33d5ec6163b1d805b6c1241ef80fed4851d76879","target":"graph","created_at":"2026-05-18T01:13:38Z","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 this paper, we consider Bayesian variable selection problem of linear regression model with global-local shrinkage priors on the regression coefficients. We propose a variable selection procedure that select a variable if the ratio of the posterior mean to the ordinary least square estimate of the corresponding coefficient is greater than $1/2$. Under the assumption of orthogonal designs, we show that if the local parameters have polynomial-tailed priors, our proposed method enjoys the oracle property in the sense that it can achieve variable selection consistency and optimal estimation rat","authors_text":"Malay Ghosh, Prasenjit Ghosh, Xiaofan Xu, Xueying Tang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-05-25T17:49:12Z","title":"Bayesian Variable Selection and Estimation Based on Global-Local Shrinkage Priors"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.07981","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":"sha256:3186bc4485f92c12b8475ea382e64f312db17dd4d789aa609aa3110d5a9b56f3","target":"record","created_at":"2026-05-18T01:13:38Z","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":"91b41d137fbccb57df210142f5ccbdc2f57a74f7f28c195f7ee1517eb451d9dc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-05-25T17:49:12Z","title_canon_sha256":"13039c4999becb4cb1a3e28588b2bb30e718c45a3af093036a28eee1b589ebc8"},"schema_version":"1.0","source":{"id":"1605.07981","kind":"arxiv","version":1}},"canonical_sha256":"c375e12d8f80d8c6675b63fec7421d1314d4bf7c87484b14e68bc37aa43219f2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c375e12d8f80d8c6675b63fec7421d1314d4bf7c87484b14e68bc37aa43219f2","first_computed_at":"2026-05-18T01:13:38.662819Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:13:38.662819Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"10urr2WvpyEB76LtRUvbYlLu9FEUbFxnuC1iYOuEEA+uYSMIr1FT8dWtRpF22GfQUR5WkG9Cv1QDrp/4NVJ/Aw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:13:38.663486Z","signed_message":"canonical_sha256_bytes"},"source_id":"1605.07981","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3186bc4485f92c12b8475ea382e64f312db17dd4d789aa609aa3110d5a9b56f3","sha256:ef77bd330c790f45eaa2459d33d5ec6163b1d805b6c1241ef80fed4851d76879"],"state_sha256":"702cb5757a7f24d061a7f0378d08d34fbcee550b8b500574f833316ba4babe5c"}