{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:ZRRY6RD6SBDHT5PD275NILFLES","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":"40b9b90e93123338d7b31c94ffdf2fbba8a1816549dfdf9689da51da0f5a9ac4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-10-31T13:32:00Z","title_canon_sha256":"df73701ba089a215c8f5b67c542ae75ca56fda527bb2c3d53a013b5ae116435a"},"schema_version":"1.0","source":{"id":"1710.11459","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.11459","created_at":"2026-05-17T23:55:43Z"},{"alias_kind":"arxiv_version","alias_value":"1710.11459v4","created_at":"2026-05-17T23:55:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.11459","created_at":"2026-05-17T23:55:43Z"},{"alias_kind":"pith_short_12","alias_value":"ZRRY6RD6SBDH","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZRRY6RD6SBDHT5PD","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZRRY6RD6","created_at":"2026-05-18T12:31:59Z"}],"graph_snapshots":[{"event_id":"sha256:aea27e38fbb096334bd314d03f8b696f3ea075148d7eaf93259cb7cf77a92c99","target":"graph","created_at":"2026-05-17T23:55:43Z","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":"The popularity of penalized regression in high-dimensional data analysis has led to a demand for new inferential tools for these models. False discovery rate control is widely used in high-dimensional hypothesis testing, but has only recently been considered in the context of penalized regression. Almost all of this work, however, has focused on lasso-penalized linear regression. In this paper, we derive a general method for controlling the marginal false discovery rate that can be applied to any penalized likelihood-based model, such as logistic regression and Cox regression. Our approach is ","authors_text":"Patrick Breheny, Ryan Miller","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-10-31T13:32:00Z","title":"Marginal false discovery rate control for likelihood-based penalized regression models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.11459","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":"sha256:5f6ac606f10d9657c4af7c0e7e41e401ceaf4adf83d78e331b1bea9ad2757406","target":"record","created_at":"2026-05-17T23:55:43Z","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":"40b9b90e93123338d7b31c94ffdf2fbba8a1816549dfdf9689da51da0f5a9ac4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-10-31T13:32:00Z","title_canon_sha256":"df73701ba089a215c8f5b67c542ae75ca56fda527bb2c3d53a013b5ae116435a"},"schema_version":"1.0","source":{"id":"1710.11459","kind":"arxiv","version":4}},"canonical_sha256":"cc638f447e904679f5e3d7fad42cab24a655ead0ef87254198cd997b9f0fd991","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cc638f447e904679f5e3d7fad42cab24a655ead0ef87254198cd997b9f0fd991","first_computed_at":"2026-05-17T23:55:43.153947Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:55:43.153947Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"evCI8C0ohuEk1OVgZrhySCBo71GUxyQoHiUGLcE1Tp3QUtddy54grXyfeK0mhlX0FlHzfY/DtDBqpnr3nFYFAA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:55:43.154671Z","signed_message":"canonical_sha256_bytes"},"source_id":"1710.11459","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5f6ac606f10d9657c4af7c0e7e41e401ceaf4adf83d78e331b1bea9ad2757406","sha256:aea27e38fbb096334bd314d03f8b696f3ea075148d7eaf93259cb7cf77a92c99"],"state_sha256":"cc99756b03df3ee7050f8ceb2d36006276e2a2b51d3597b09509e9efd3888540"}