{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:NEQPX3SPRSJJQRMYSZJQKKIF4C","short_pith_number":"pith:NEQPX3SP","canonical_record":{"source":{"id":"1401.3084","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-01-14T06:47:59Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"9c6c1715571932881f22958026076dc4e9651d42e18523650a682feabfe0da62","abstract_canon_sha256":"f8856b9aab752bcea6a9e019545d2911fdf950d648a9c888119a193597c2ef86"},"schema_version":"1.0"},"canonical_sha256":"6920fbee4f8c929845989653052905e0948ff36c432da7a59f6f87e35b6c101e","source":{"kind":"arxiv","id":"1401.3084","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1401.3084","created_at":"2026-05-18T00:32:45Z"},{"alias_kind":"arxiv_version","alias_value":"1401.3084v1","created_at":"2026-05-18T00:32:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1401.3084","created_at":"2026-05-18T00:32:45Z"},{"alias_kind":"pith_short_12","alias_value":"NEQPX3SPRSJJ","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_16","alias_value":"NEQPX3SPRSJJQRMY","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_8","alias_value":"NEQPX3SP","created_at":"2026-05-18T12:28:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:NEQPX3SPRSJJQRMYSZJQKKIF4C","target":"record","payload":{"canonical_record":{"source":{"id":"1401.3084","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-01-14T06:47:59Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"9c6c1715571932881f22958026076dc4e9651d42e18523650a682feabfe0da62","abstract_canon_sha256":"f8856b9aab752bcea6a9e019545d2911fdf950d648a9c888119a193597c2ef86"},"schema_version":"1.0"},"canonical_sha256":"6920fbee4f8c929845989653052905e0948ff36c432da7a59f6f87e35b6c101e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:32:45.386546Z","signature_b64":"is1Xk7EYJhQfbEmYCV6ZDDPajxjWtN49PLfsgWa6r4ENxCt7GG6HZYQWYWCl3BQ1U8vjpTOQ+sJytweCMAWmAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6920fbee4f8c929845989653052905e0948ff36c432da7a59f6f87e35b6c101e","last_reissued_at":"2026-05-18T00:32:45.385870Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:32:45.385870Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1401.3084","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":"2026-05-18T00:32:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hPAPO8W/JtCih4Bg555GlVpyHyViJZ+FYnyvvXZ/HowSYTuKyV/+VE89syPCqZv5ezRmnDzjmBmrUA1xa9GeDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T09:38:39.376732Z"},"content_sha256":"14cbb89b6a6461cda99a8fe4861f0c4e2aef54c15b39d3e435c7e0ae5bde7e1a","schema_version":"1.0","event_id":"sha256:14cbb89b6a6461cda99a8fe4861f0c4e2aef54c15b39d3e435c7e0ae5bde7e1a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:NEQPX3SPRSJJQRMYSZJQKKIF4C","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A comparison of Bayesian and frequentist interval estimators in regression that utilize uncertain prior information","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME","stat.TH"],"primary_cat":"math.ST","authors_text":"Gayan Dharmarathne, Paul Kabaila","submitted_at":"2014-01-14T06:47:59Z","abstract_excerpt":"Consider a linear regression model with regression parameter beta and normally distributed errors. Suppose that the parameter of interest is theta = a^T beta where a is a specified vector. Define the parameter tau = c^T beta - t where c and t are specified and a and c are linearly independent. Also suppose that we have uncertain prior information that tau = 0. Kabaila and Giri, 2009, JSPI, describe a new frequentist 1-alpha confidence interval for theta that utilizes this uncertain prior information. We compare this confidence interval with Bayesian 1-alpha equi-tailed and shortest credible in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1401.3084","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":"2026-05-18T00:32:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/DpGkR5PThUukakLn0tyyW2RFnpyCs+aYR/kCZtTkwpSg5qoeKE33moFEjx4p3jseRw7qp3zocEPStvHOPU5Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T09:38:39.377074Z"},"content_sha256":"135fbb8712509d319556e0e2767e082ce103ac0555c497189626ff3bf1da086a","schema_version":"1.0","event_id":"sha256:135fbb8712509d319556e0e2767e082ce103ac0555c497189626ff3bf1da086a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NEQPX3SPRSJJQRMYSZJQKKIF4C/bundle.json","state_url":"https://pith.science/pith/NEQPX3SPRSJJQRMYSZJQKKIF4C/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NEQPX3SPRSJJQRMYSZJQKKIF4C/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":"2026-06-26T09:38:39Z","links":{"resolver":"https://pith.science/pith/NEQPX3SPRSJJQRMYSZJQKKIF4C","bundle":"https://pith.science/pith/NEQPX3SPRSJJQRMYSZJQKKIF4C/bundle.json","state":"https://pith.science/pith/NEQPX3SPRSJJQRMYSZJQKKIF4C/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NEQPX3SPRSJJQRMYSZJQKKIF4C/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:NEQPX3SPRSJJQRMYSZJQKKIF4C","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":"f8856b9aab752bcea6a9e019545d2911fdf950d648a9c888119a193597c2ef86","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-01-14T06:47:59Z","title_canon_sha256":"9c6c1715571932881f22958026076dc4e9651d42e18523650a682feabfe0da62"},"schema_version":"1.0","source":{"id":"1401.3084","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1401.3084","created_at":"2026-05-18T00:32:45Z"},{"alias_kind":"arxiv_version","alias_value":"1401.3084v1","created_at":"2026-05-18T00:32:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1401.3084","created_at":"2026-05-18T00:32:45Z"},{"alias_kind":"pith_short_12","alias_value":"NEQPX3SPRSJJ","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_16","alias_value":"NEQPX3SPRSJJQRMY","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_8","alias_value":"NEQPX3SP","created_at":"2026-05-18T12:28:41Z"}],"graph_snapshots":[{"event_id":"sha256:135fbb8712509d319556e0e2767e082ce103ac0555c497189626ff3bf1da086a","target":"graph","created_at":"2026-05-18T00:32:45Z","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":"Consider a linear regression model with regression parameter beta and normally distributed errors. Suppose that the parameter of interest is theta = a^T beta where a is a specified vector. Define the parameter tau = c^T beta - t where c and t are specified and a and c are linearly independent. Also suppose that we have uncertain prior information that tau = 0. Kabaila and Giri, 2009, JSPI, describe a new frequentist 1-alpha confidence interval for theta that utilizes this uncertain prior information. We compare this confidence interval with Bayesian 1-alpha equi-tailed and shortest credible in","authors_text":"Gayan Dharmarathne, Paul Kabaila","cross_cats":["stat.ME","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-01-14T06:47:59Z","title":"A comparison of Bayesian and frequentist interval estimators in regression that utilize uncertain prior information"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1401.3084","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":"sha256:14cbb89b6a6461cda99a8fe4861f0c4e2aef54c15b39d3e435c7e0ae5bde7e1a","target":"record","created_at":"2026-05-18T00:32:45Z","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":"f8856b9aab752bcea6a9e019545d2911fdf950d648a9c888119a193597c2ef86","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2014-01-14T06:47:59Z","title_canon_sha256":"9c6c1715571932881f22958026076dc4e9651d42e18523650a682feabfe0da62"},"schema_version":"1.0","source":{"id":"1401.3084","kind":"arxiv","version":1}},"canonical_sha256":"6920fbee4f8c929845989653052905e0948ff36c432da7a59f6f87e35b6c101e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6920fbee4f8c929845989653052905e0948ff36c432da7a59f6f87e35b6c101e","first_computed_at":"2026-05-18T00:32:45.385870Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:32:45.385870Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"is1Xk7EYJhQfbEmYCV6ZDDPajxjWtN49PLfsgWa6r4ENxCt7GG6HZYQWYWCl3BQ1U8vjpTOQ+sJytweCMAWmAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:32:45.386546Z","signed_message":"canonical_sha256_bytes"},"source_id":"1401.3084","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:14cbb89b6a6461cda99a8fe4861f0c4e2aef54c15b39d3e435c7e0ae5bde7e1a","sha256:135fbb8712509d319556e0e2767e082ce103ac0555c497189626ff3bf1da086a"],"state_sha256":"951eabc6a6e41884d48426e9c92b127446d4ff69e57ef48b124113931cdcb938"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"if/dosYbqd4VjwG/uvXicC35MYyzLuAXdhOiFx1g+1gUr0u/i5UvF057Yv68IIcJUlF+PeUYNx9S+/ctiHiZBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-26T09:38:39.378978Z","bundle_sha256":"d77a03eddb0e115c3e345db39b27fcaf576f85eeda10aa792d774de4cd3aff46"}}