{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:G2VKG6ZGNQTC7SVYYAIKNQPUAF","short_pith_number":"pith:G2VKG6ZG","schema_version":"1.0","canonical_sha256":"36aaa37b266c262fcab8c010a6c1f4015eea314bb3467ee12b247c94c3d52afb","source":{"kind":"arxiv","id":"1709.10505","version":1},"attestation_state":"computed","paper":{"title":"Discriminating between two models based on Bregman divergence in small samples","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Carlos Simplice Ogouyandjou, Jean de Dieu Nkurunziza, Papa Ngom","submitted_at":"2017-09-29T17:31:08Z","abstract_excerpt":"Recently in [1, 2], Ali-Akbar Bromideh introduced the Kullback-Leibler Divergence (KLD) test statistic in discrim- inating between two models. It was found that the Ratio Minimized Kulback-Leibler Divergence (RMKLD) works better than the Ratio of Maximized Likelihood (RML) for small sample size. The aim of this paper is to generalize the works of Ali-Akbar Bromideh by proposing a hypothesis testing based on Bregman divergence in order to improve the process of choice of the model. Our aproach differs from him. After observing n data points of unknown density f ; we firstly measure the closness"},"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":"1709.10505","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-09-29T17:31:08Z","cross_cats_sorted":[],"title_canon_sha256":"31b555d9c060a1b4300d1623bb0a1f005dfe0d5359fed97b9df79143eecb0822","abstract_canon_sha256":"7abbcc00fec93824a7a0c15e08e50436ba26e1729ab9550f6a301d509019a384"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:34:00.862584Z","signature_b64":"BsdAmY5aECRu+2aTtlXD39Hw3NKh18wPNu+9cb0b2Z0GoFAik1t9PKoIkTBzF8UNRSavJ7ODcS57BciIHt1kDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"36aaa37b266c262fcab8c010a6c1f4015eea314bb3467ee12b247c94c3d52afb","last_reissued_at":"2026-05-18T00:34:00.861867Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:34:00.861867Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Discriminating between two models based on Bregman divergence in small samples","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Carlos Simplice Ogouyandjou, Jean de Dieu Nkurunziza, Papa Ngom","submitted_at":"2017-09-29T17:31:08Z","abstract_excerpt":"Recently in [1, 2], Ali-Akbar Bromideh introduced the Kullback-Leibler Divergence (KLD) test statistic in discrim- inating between two models. It was found that the Ratio Minimized Kulback-Leibler Divergence (RMKLD) works better than the Ratio of Maximized Likelihood (RML) for small sample size. The aim of this paper is to generalize the works of Ali-Akbar Bromideh by proposing a hypothesis testing based on Bregman divergence in order to improve the process of choice of the model. Our aproach differs from him. After observing n data points of unknown density f ; we firstly measure the closness"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.10505","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":"1709.10505","created_at":"2026-05-18T00:34:00.861985+00:00"},{"alias_kind":"arxiv_version","alias_value":"1709.10505v1","created_at":"2026-05-18T00:34:00.861985+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.10505","created_at":"2026-05-18T00:34:00.861985+00:00"},{"alias_kind":"pith_short_12","alias_value":"G2VKG6ZGNQTC","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_16","alias_value":"G2VKG6ZGNQTC7SVY","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_8","alias_value":"G2VKG6ZG","created_at":"2026-05-18T12:31:15.632608+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/G2VKG6ZGNQTC7SVYYAIKNQPUAF","json":"https://pith.science/pith/G2VKG6ZGNQTC7SVYYAIKNQPUAF.json","graph_json":"https://pith.science/api/pith-number/G2VKG6ZGNQTC7SVYYAIKNQPUAF/graph.json","events_json":"https://pith.science/api/pith-number/G2VKG6ZGNQTC7SVYYAIKNQPUAF/events.json","paper":"https://pith.science/paper/G2VKG6ZG"},"agent_actions":{"view_html":"https://pith.science/pith/G2VKG6ZGNQTC7SVYYAIKNQPUAF","download_json":"https://pith.science/pith/G2VKG6ZGNQTC7SVYYAIKNQPUAF.json","view_paper":"https://pith.science/paper/G2VKG6ZG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1709.10505&json=true","fetch_graph":"https://pith.science/api/pith-number/G2VKG6ZGNQTC7SVYYAIKNQPUAF/graph.json","fetch_events":"https://pith.science/api/pith-number/G2VKG6ZGNQTC7SVYYAIKNQPUAF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/G2VKG6ZGNQTC7SVYYAIKNQPUAF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/G2VKG6ZGNQTC7SVYYAIKNQPUAF/action/storage_attestation","attest_author":"https://pith.science/pith/G2VKG6ZGNQTC7SVYYAIKNQPUAF/action/author_attestation","sign_citation":"https://pith.science/pith/G2VKG6ZGNQTC7SVYYAIKNQPUAF/action/citation_signature","submit_replication":"https://pith.science/pith/G2VKG6ZGNQTC7SVYYAIKNQPUAF/action/replication_record"}},"created_at":"2026-05-18T00:34:00.861985+00:00","updated_at":"2026-05-18T00:34:00.861985+00:00"}