{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:S2I34TKMZHYGE3MGVC2ZVVOJDF","short_pith_number":"pith:S2I34TKM","schema_version":"1.0","canonical_sha256":"9691be4d4cc9f0626d86a8b59ad5c919601b9648b3056b76aca8fe06e02b5f93","source":{"kind":"arxiv","id":"1507.08645","version":2},"attestation_state":"computed","paper":{"title":"Moment conditions and Bayesian nonparametrics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.PR","math.ST","stat.AP","stat.CO","stat.TH"],"primary_cat":"stat.ME","authors_text":"Luke Bornn, Neil Shephard, Reza Solgi","submitted_at":"2015-07-30T19:45:52Z","abstract_excerpt":"Models phrased though moment conditions are central to much of modern inference. Here these moment conditions are embedded within a nonparametric Bayesian setup. Handling such a model is not probabilistically straightforward as the posterior has support on a manifold. We solve the relevant issues, building new probability and computational tools using Hausdorff measures to analyze them on real and simulated data. These new methods which involve simulating on a manifold can be applied widely, including providing Bayesian analysis of quasi-likelihoods, linear and nonlinear regression, missing da"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1507.08645","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2015-07-30T19:45:52Z","cross_cats_sorted":["math.PR","math.ST","stat.AP","stat.CO","stat.TH"],"title_canon_sha256":"526f777dc058dbc4d5788b38bf224fac9fb07599267edf9d87ac0af2fdd8dccd","abstract_canon_sha256":"e8e5ab15fde0423dc85c7b938c225a3d7315c2c30d935df925d09198f1e4cd7c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:22:57.639147Z","signature_b64":"tBaNv/nvP24fyl4UzkBJK2Nvxy7kX7D3iJXmSZMP9gcRS51fkzwb7M1wiPQKSCbI0K658XcvnGKoCnfsvpMKBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9691be4d4cc9f0626d86a8b59ad5c919601b9648b3056b76aca8fe06e02b5f93","last_reissued_at":"2026-05-18T01:22:57.638700Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:22:57.638700Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Moment conditions and Bayesian nonparametrics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.PR","math.ST","stat.AP","stat.CO","stat.TH"],"primary_cat":"stat.ME","authors_text":"Luke Bornn, Neil Shephard, Reza Solgi","submitted_at":"2015-07-30T19:45:52Z","abstract_excerpt":"Models phrased though moment conditions are central to much of modern inference. Here these moment conditions are embedded within a nonparametric Bayesian setup. Handling such a model is not probabilistically straightforward as the posterior has support on a manifold. We solve the relevant issues, building new probability and computational tools using Hausdorff measures to analyze them on real and simulated data. These new methods which involve simulating on a manifold can be applied widely, including providing Bayesian analysis of quasi-likelihoods, linear and nonlinear regression, missing da"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1507.08645","kind":"arxiv","version":2},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1507.08645","created_at":"2026-05-18T01:22:57.638765+00:00"},{"alias_kind":"arxiv_version","alias_value":"1507.08645v2","created_at":"2026-05-18T01:22:57.638765+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1507.08645","created_at":"2026-05-18T01:22:57.638765+00:00"},{"alias_kind":"pith_short_12","alias_value":"S2I34TKMZHYG","created_at":"2026-05-18T12:29:39.896362+00:00"},{"alias_kind":"pith_short_16","alias_value":"S2I34TKMZHYGE3MG","created_at":"2026-05-18T12:29:39.896362+00:00"},{"alias_kind":"pith_short_8","alias_value":"S2I34TKM","created_at":"2026-05-18T12:29:39.896362+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/S2I34TKMZHYGE3MGVC2ZVVOJDF","json":"https://pith.science/pith/S2I34TKMZHYGE3MGVC2ZVVOJDF.json","graph_json":"https://pith.science/api/pith-number/S2I34TKMZHYGE3MGVC2ZVVOJDF/graph.json","events_json":"https://pith.science/api/pith-number/S2I34TKMZHYGE3MGVC2ZVVOJDF/events.json","paper":"https://pith.science/paper/S2I34TKM"},"agent_actions":{"view_html":"https://pith.science/pith/S2I34TKMZHYGE3MGVC2ZVVOJDF","download_json":"https://pith.science/pith/S2I34TKMZHYGE3MGVC2ZVVOJDF.json","view_paper":"https://pith.science/paper/S2I34TKM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1507.08645&json=true","fetch_graph":"https://pith.science/api/pith-number/S2I34TKMZHYGE3MGVC2ZVVOJDF/graph.json","fetch_events":"https://pith.science/api/pith-number/S2I34TKMZHYGE3MGVC2ZVVOJDF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/S2I34TKMZHYGE3MGVC2ZVVOJDF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/S2I34TKMZHYGE3MGVC2ZVVOJDF/action/storage_attestation","attest_author":"https://pith.science/pith/S2I34TKMZHYGE3MGVC2ZVVOJDF/action/author_attestation","sign_citation":"https://pith.science/pith/S2I34TKMZHYGE3MGVC2ZVVOJDF/action/citation_signature","submit_replication":"https://pith.science/pith/S2I34TKMZHYGE3MGVC2ZVVOJDF/action/replication_record"}},"created_at":"2026-05-18T01:22:57.638765+00:00","updated_at":"2026-05-18T01:22:57.638765+00:00"}