{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:24FESTPOZ2IWGTTG7XLC6ETVK4","short_pith_number":"pith:24FESTPO","schema_version":"1.0","canonical_sha256":"d70a494deece91634e66fdd62f1275570c8393ec0fba56440813fc66f6cd995c","source":{"kind":"arxiv","id":"1711.00136","version":2},"attestation_state":"computed","paper":{"title":"Bayesian model comparison with the Hyv\\\"arinen score: computation and consistency","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Jie Ding, Pierre E. Jacob, Stephane Shao, Vahid Tarokh","submitted_at":"2017-10-31T22:50:32Z","abstract_excerpt":"The Bayes factor is a widely used criterion in model comparison and its logarithm is a difference of out-of-sample predictive scores under the logarithmic scoring rule. However, when some of the candidate models involve vague priors on their parameters, the log-Bayes factor features an arbitrary additive constant that hinders its interpretation. As an alternative, we consider model comparison using the Hyv\\\"arinen score. We propose a method to consistently estimate this score for parametric models, using sequential Monte Carlo methods. We show that this score can be estimated for models with t"},"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":"1711.00136","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-10-31T22:50:32Z","cross_cats_sorted":[],"title_canon_sha256":"15d5127ddd7577cfdb3871ec977a14e0d0ed37f367910375199953602f3e3803","abstract_canon_sha256":"86e73d9a396e8d149fd9dd659042ee56e0861857d50bc32f5cb0f3bd796ffccd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:06:25.409993Z","signature_b64":"lMRNsOCKVFO2ZdeIbgoKw8AlWn+j4sXgaf+5/X912tfVoR4oXEDHvBgd4jAkuvOk5fe4j6UEyrsGdnkFmS96DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d70a494deece91634e66fdd62f1275570c8393ec0fba56440813fc66f6cd995c","last_reissued_at":"2026-05-18T00:06:25.409346Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:06:25.409346Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Bayesian model comparison with the Hyv\\\"arinen score: computation and consistency","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Jie Ding, Pierre E. Jacob, Stephane Shao, Vahid Tarokh","submitted_at":"2017-10-31T22:50:32Z","abstract_excerpt":"The Bayes factor is a widely used criterion in model comparison and its logarithm is a difference of out-of-sample predictive scores under the logarithmic scoring rule. However, when some of the candidate models involve vague priors on their parameters, the log-Bayes factor features an arbitrary additive constant that hinders its interpretation. As an alternative, we consider model comparison using the Hyv\\\"arinen score. We propose a method to consistently estimate this score for parametric models, using sequential Monte Carlo methods. We show that this score can be estimated for models with t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.00136","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":"1711.00136","created_at":"2026-05-18T00:06:25.409441+00:00"},{"alias_kind":"arxiv_version","alias_value":"1711.00136v2","created_at":"2026-05-18T00:06:25.409441+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.00136","created_at":"2026-05-18T00:06:25.409441+00:00"},{"alias_kind":"pith_short_12","alias_value":"24FESTPOZ2IW","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_16","alias_value":"24FESTPOZ2IWGTTG","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_8","alias_value":"24FESTPO","created_at":"2026-05-18T12:30:55.937587+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/24FESTPOZ2IWGTTG7XLC6ETVK4","json":"https://pith.science/pith/24FESTPOZ2IWGTTG7XLC6ETVK4.json","graph_json":"https://pith.science/api/pith-number/24FESTPOZ2IWGTTG7XLC6ETVK4/graph.json","events_json":"https://pith.science/api/pith-number/24FESTPOZ2IWGTTG7XLC6ETVK4/events.json","paper":"https://pith.science/paper/24FESTPO"},"agent_actions":{"view_html":"https://pith.science/pith/24FESTPOZ2IWGTTG7XLC6ETVK4","download_json":"https://pith.science/pith/24FESTPOZ2IWGTTG7XLC6ETVK4.json","view_paper":"https://pith.science/paper/24FESTPO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1711.00136&json=true","fetch_graph":"https://pith.science/api/pith-number/24FESTPOZ2IWGTTG7XLC6ETVK4/graph.json","fetch_events":"https://pith.science/api/pith-number/24FESTPOZ2IWGTTG7XLC6ETVK4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/24FESTPOZ2IWGTTG7XLC6ETVK4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/24FESTPOZ2IWGTTG7XLC6ETVK4/action/storage_attestation","attest_author":"https://pith.science/pith/24FESTPOZ2IWGTTG7XLC6ETVK4/action/author_attestation","sign_citation":"https://pith.science/pith/24FESTPOZ2IWGTTG7XLC6ETVK4/action/citation_signature","submit_replication":"https://pith.science/pith/24FESTPOZ2IWGTTG7XLC6ETVK4/action/replication_record"}},"created_at":"2026-05-18T00:06:25.409441+00:00","updated_at":"2026-05-18T00:06:25.409441+00:00"}