{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:HIKM5FW2WJGVCIY62QGSOX6CP7","short_pith_number":"pith:HIKM5FW2","schema_version":"1.0","canonical_sha256":"3a14ce96dab24d51231ed40d275fc27fca4b9f2625c91d10315dcfb58cd2c0b5","source":{"kind":"arxiv","id":"1501.07091","version":1},"attestation_state":"computed","paper":{"title":"Forward-reverse EM algorithm for Markov chains: convergence and numerical analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.NA","stat.TH"],"primary_cat":"math.ST","authors_text":"Christian Bayer, Hilmar Mai, John Schoenmakers","submitted_at":"2015-01-28T13:01:37Z","abstract_excerpt":"We develop a forward-reverse EM (FREM) algorithm for estimating parameters that determine the dynamics of a discrete time Markov chain evolving through a certain measurable state space. As a key tool for the construction of the FREM method we develop forward-reverse representations for Markov chains conditioned on a certain terminal state. These representations may be considered as an extension of the earlier work Bayer and Schoenmakers [2013] on conditional diffusions. We proof almost sure convergence of our algorithm for a Markov chain model with curved exponential family structure. On the n"},"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":"1501.07091","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2015-01-28T13:01:37Z","cross_cats_sorted":["math.NA","stat.TH"],"title_canon_sha256":"3d1cde0a6a34cb787e2ace9bf8e0e0dcabb7685929502c3d0a71e72b7f71fbaa","abstract_canon_sha256":"10ccfadf24aab474c2fab22333b0fa82e0c426484c66e6cceed14547552bb211"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:28:30.298028Z","signature_b64":"zC2GzlMSYaNLcpa+4yK5wyfwmir92KTpUui1lTbOAydkkmBcE3LG2NY+JGj5PwqUVD7O1/eYKyQZw+LzGtAqBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3a14ce96dab24d51231ed40d275fc27fca4b9f2625c91d10315dcfb58cd2c0b5","last_reissued_at":"2026-05-18T02:28:30.297483Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:28:30.297483Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Forward-reverse EM algorithm for Markov chains: convergence and numerical analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.NA","stat.TH"],"primary_cat":"math.ST","authors_text":"Christian Bayer, Hilmar Mai, John Schoenmakers","submitted_at":"2015-01-28T13:01:37Z","abstract_excerpt":"We develop a forward-reverse EM (FREM) algorithm for estimating parameters that determine the dynamics of a discrete time Markov chain evolving through a certain measurable state space. As a key tool for the construction of the FREM method we develop forward-reverse representations for Markov chains conditioned on a certain terminal state. These representations may be considered as an extension of the earlier work Bayer and Schoenmakers [2013] on conditional diffusions. We proof almost sure convergence of our algorithm for a Markov chain model with curved exponential family structure. On the n"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1501.07091","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1501.07091","created_at":"2026-05-18T02:28:30.297551+00:00"},{"alias_kind":"arxiv_version","alias_value":"1501.07091v1","created_at":"2026-05-18T02:28:30.297551+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1501.07091","created_at":"2026-05-18T02:28:30.297551+00:00"},{"alias_kind":"pith_short_12","alias_value":"HIKM5FW2WJGV","created_at":"2026-05-18T12:29:25.134429+00:00"},{"alias_kind":"pith_short_16","alias_value":"HIKM5FW2WJGVCIY6","created_at":"2026-05-18T12:29:25.134429+00:00"},{"alias_kind":"pith_short_8","alias_value":"HIKM5FW2","created_at":"2026-05-18T12:29:25.134429+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/HIKM5FW2WJGVCIY62QGSOX6CP7","json":"https://pith.science/pith/HIKM5FW2WJGVCIY62QGSOX6CP7.json","graph_json":"https://pith.science/api/pith-number/HIKM5FW2WJGVCIY62QGSOX6CP7/graph.json","events_json":"https://pith.science/api/pith-number/HIKM5FW2WJGVCIY62QGSOX6CP7/events.json","paper":"https://pith.science/paper/HIKM5FW2"},"agent_actions":{"view_html":"https://pith.science/pith/HIKM5FW2WJGVCIY62QGSOX6CP7","download_json":"https://pith.science/pith/HIKM5FW2WJGVCIY62QGSOX6CP7.json","view_paper":"https://pith.science/paper/HIKM5FW2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1501.07091&json=true","fetch_graph":"https://pith.science/api/pith-number/HIKM5FW2WJGVCIY62QGSOX6CP7/graph.json","fetch_events":"https://pith.science/api/pith-number/HIKM5FW2WJGVCIY62QGSOX6CP7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HIKM5FW2WJGVCIY62QGSOX6CP7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HIKM5FW2WJGVCIY62QGSOX6CP7/action/storage_attestation","attest_author":"https://pith.science/pith/HIKM5FW2WJGVCIY62QGSOX6CP7/action/author_attestation","sign_citation":"https://pith.science/pith/HIKM5FW2WJGVCIY62QGSOX6CP7/action/citation_signature","submit_replication":"https://pith.science/pith/HIKM5FW2WJGVCIY62QGSOX6CP7/action/replication_record"}},"created_at":"2026-05-18T02:28:30.297551+00:00","updated_at":"2026-05-18T02:28:30.297551+00:00"}