{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:NYXNXCO3MIVI2DMPB7KXIEJHBB","short_pith_number":"pith:NYXNXCO3","canonical_record":{"source":{"id":"1903.05367","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2019-03-13T09:01:43Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"b1ff9adf310ff658fd933e620abb2afb60109874bc63a9810da778d487b3a331","abstract_canon_sha256":"1aa99c5be9e7fe8a1e96a46ec1a02257cc16b530a71d9a7fac50542c9225b744"},"schema_version":"1.0"},"canonical_sha256":"6e2edb89db622a8d0d8f0fd5741127085448810b8f3818b81fecb65d35a7605f","source":{"kind":"arxiv","id":"1903.05367","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.05367","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"arxiv_version","alias_value":"1903.05367v1","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.05367","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"pith_short_12","alias_value":"NYXNXCO3MIVI","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"NYXNXCO3MIVI2DMP","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"NYXNXCO3","created_at":"2026-05-18T12:33:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:NYXNXCO3MIVI2DMPB7KXIEJHBB","target":"record","payload":{"canonical_record":{"source":{"id":"1903.05367","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2019-03-13T09:01:43Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"b1ff9adf310ff658fd933e620abb2afb60109874bc63a9810da778d487b3a331","abstract_canon_sha256":"1aa99c5be9e7fe8a1e96a46ec1a02257cc16b530a71d9a7fac50542c9225b744"},"schema_version":"1.0"},"canonical_sha256":"6e2edb89db622a8d0d8f0fd5741127085448810b8f3818b81fecb65d35a7605f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:24.510445Z","signature_b64":"CISSqJQ4KvPEGRblQYCSSdSBdkMDjM0n1dtrVWLtGP5lEXR2PyDQWwSSFurRL6FkKRQ2LWsMKNjAM/kCy22NBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6e2edb89db622a8d0d8f0fd5741127085448810b8f3818b81fecb65d35a7605f","last_reissued_at":"2026-05-17T23:51:24.509866Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:24.509866Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.05367","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:51:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iLy9b1x1Ca4dre0hPnjdlT4ofE57CZj/7hdxCj0zN2Pvqflubhex+etT0iCreS0XjucOjcgBwENqa3TtFiWbCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T07:33:40.982651Z"},"content_sha256":"a7aaae9dd79cbfdfad7366c680f67015f5992879b06ba6219f004bbd742c7c41","schema_version":"1.0","event_id":"sha256:a7aaae9dd79cbfdfad7366c680f67015f5992879b06ba6219f004bbd742c7c41"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:NYXNXCO3MIVI2DMPB7KXIEJHBB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A novel Bayesian approach for variable selection in linear regression models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"stat.CO","authors_text":"J\\\"urgen Pilz, Konstantin Posch, Maximilian Arbeiter","submitted_at":"2019-03-13T09:01:43Z","abstract_excerpt":"We propose a novel Bayesian approach to the problem of variable selection in multiple linear regression models. In particular, we present a hierarchical setting which allows for direct specification of a-priori beliefs about the number of nonzero regression coefficients as well as a specification of beliefs that given coefficients are nonzero. To guarantee numerical stability, we adopt a $g$-prior with an additional ridge parameter for the unknown regression coefficients. In order to simulate from the joint posterior distribution an intelligent random walk Metropolis-Hastings algorithm which i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.05367","kind":"arxiv","version":1},"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":"2026-05-17T23:51:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8nkw1v5FDxIM5TySvtSC7vDQIdP1RbBJX3H0yECBK2mW75xyjj/zC7W4Zt0KeWsXBGe3oAEL/KN3owr9EfS9Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T07:33:40.983088Z"},"content_sha256":"f8dca94043a89bc2652392773becd4a66ee84ec97077d208c6acf153a3a037d8","schema_version":"1.0","event_id":"sha256:f8dca94043a89bc2652392773becd4a66ee84ec97077d208c6acf153a3a037d8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NYXNXCO3MIVI2DMPB7KXIEJHBB/bundle.json","state_url":"https://pith.science/pith/NYXNXCO3MIVI2DMPB7KXIEJHBB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NYXNXCO3MIVI2DMPB7KXIEJHBB/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":"2026-06-24T07:33:40Z","links":{"resolver":"https://pith.science/pith/NYXNXCO3MIVI2DMPB7KXIEJHBB","bundle":"https://pith.science/pith/NYXNXCO3MIVI2DMPB7KXIEJHBB/bundle.json","state":"https://pith.science/pith/NYXNXCO3MIVI2DMPB7KXIEJHBB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NYXNXCO3MIVI2DMPB7KXIEJHBB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:NYXNXCO3MIVI2DMPB7KXIEJHBB","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":"1aa99c5be9e7fe8a1e96a46ec1a02257cc16b530a71d9a7fac50542c9225b744","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2019-03-13T09:01:43Z","title_canon_sha256":"b1ff9adf310ff658fd933e620abb2afb60109874bc63a9810da778d487b3a331"},"schema_version":"1.0","source":{"id":"1903.05367","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.05367","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"arxiv_version","alias_value":"1903.05367v1","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.05367","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"pith_short_12","alias_value":"NYXNXCO3MIVI","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"NYXNXCO3MIVI2DMP","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"NYXNXCO3","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:f8dca94043a89bc2652392773becd4a66ee84ec97077d208c6acf153a3a037d8","target":"graph","created_at":"2026-05-17T23:51:24Z","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 propose a novel Bayesian approach to the problem of variable selection in multiple linear regression models. In particular, we present a hierarchical setting which allows for direct specification of a-priori beliefs about the number of nonzero regression coefficients as well as a specification of beliefs that given coefficients are nonzero. To guarantee numerical stability, we adopt a $g$-prior with an additional ridge parameter for the unknown regression coefficients. In order to simulate from the joint posterior distribution an intelligent random walk Metropolis-Hastings algorithm which i","authors_text":"J\\\"urgen Pilz, Konstantin Posch, Maximilian Arbeiter","cross_cats":["stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2019-03-13T09:01:43Z","title":"A novel Bayesian approach for variable selection in linear regression models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.05367","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:a7aaae9dd79cbfdfad7366c680f67015f5992879b06ba6219f004bbd742c7c41","target":"record","created_at":"2026-05-17T23:51:24Z","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":"1aa99c5be9e7fe8a1e96a46ec1a02257cc16b530a71d9a7fac50542c9225b744","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2019-03-13T09:01:43Z","title_canon_sha256":"b1ff9adf310ff658fd933e620abb2afb60109874bc63a9810da778d487b3a331"},"schema_version":"1.0","source":{"id":"1903.05367","kind":"arxiv","version":1}},"canonical_sha256":"6e2edb89db622a8d0d8f0fd5741127085448810b8f3818b81fecb65d35a7605f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6e2edb89db622a8d0d8f0fd5741127085448810b8f3818b81fecb65d35a7605f","first_computed_at":"2026-05-17T23:51:24.509866Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:51:24.509866Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CISSqJQ4KvPEGRblQYCSSdSBdkMDjM0n1dtrVWLtGP5lEXR2PyDQWwSSFurRL6FkKRQ2LWsMKNjAM/kCy22NBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:51:24.510445Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.05367","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a7aaae9dd79cbfdfad7366c680f67015f5992879b06ba6219f004bbd742c7c41","sha256:f8dca94043a89bc2652392773becd4a66ee84ec97077d208c6acf153a3a037d8"],"state_sha256":"09be0992ff6c5e14f77b015d0cc0d68e478373588e27d5ee72d42c44bbcd9b6f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6a4DlXP8QHkBbDNlOplx6yCCzcyc2qwpO9QIVwLFtnEOJY+p5xPVmY0xbV48IRMkPgDdqThLxWrT0lxe+TQmAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-24T07:33:40.985277Z","bundle_sha256":"e22981e57dbd66b7dea8cb18fe9a34833be0b8529f4db7e1efa42eaa743c75f7"}}