{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:FWDZHUZOWATK25J7TEWPDESDJG","short_pith_number":"pith:FWDZHUZO","canonical_record":{"source":{"id":"1609.07452","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-09-23T18:21:08Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"78e0ae47a6c0335e54b6a6b7e28906e462e94a837ae82aaae42d34c90b50821c","abstract_canon_sha256":"03eddb84c8b28be293a29767f2ea30e9bc936cdf088c654e4a89669425820d82"},"schema_version":"1.0"},"canonical_sha256":"2d8793d32eb026ad753f992cf192434999719d8e80706461514e62ecf73688fb","source":{"kind":"arxiv","id":"1609.07452","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1609.07452","created_at":"2026-05-17T23:46:46Z"},{"alias_kind":"arxiv_version","alias_value":"1609.07452v1","created_at":"2026-05-17T23:46:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.07452","created_at":"2026-05-17T23:46:46Z"},{"alias_kind":"pith_short_12","alias_value":"FWDZHUZOWATK","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_16","alias_value":"FWDZHUZOWATK25J7","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_8","alias_value":"FWDZHUZO","created_at":"2026-05-18T12:30:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:FWDZHUZOWATK25J7TEWPDESDJG","target":"record","payload":{"canonical_record":{"source":{"id":"1609.07452","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-09-23T18:21:08Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"78e0ae47a6c0335e54b6a6b7e28906e462e94a837ae82aaae42d34c90b50821c","abstract_canon_sha256":"03eddb84c8b28be293a29767f2ea30e9bc936cdf088c654e4a89669425820d82"},"schema_version":"1.0"},"canonical_sha256":"2d8793d32eb026ad753f992cf192434999719d8e80706461514e62ecf73688fb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:46:46.647135Z","signature_b64":"pGZW3X/ewge5BeyIMlyYl4cUM7rAChVgFCT6tyis6m1Pf5u3Ngn/Tkgr0PSPM5XtbVyV17ls1OVhaMogY17/Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2d8793d32eb026ad753f992cf192434999719d8e80706461514e62ecf73688fb","last_reissued_at":"2026-05-17T23:46:46.646572Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:46:46.646572Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1609.07452","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":"2026-05-17T23:46:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JjfgzDOzHApi7ZyTL0kgXpBsHtLb6tjZ3zqu5fpU7pATwLcuH2vvDix5A0wpdv0Mi3EqHzZVX/2oAoe5i8YjAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T05:35:54.522432Z"},"content_sha256":"626e7bf283d8e7ed4807003137dbffbd957dec6388779b239086d4f2a239154a","schema_version":"1.0","event_id":"sha256:626e7bf283d8e7ed4807003137dbffbd957dec6388779b239086d4f2a239154a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:FWDZHUZOWATK25J7TEWPDESDJG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Wald-type test statistic for testing linear hypothesis in logistic regression models based on minimum density power divergence estimator","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Abhijit Mandal, Abhik Ghosh, Ayandrendanath Basu, Leandro Pardo, Nirian Martin","submitted_at":"2016-09-23T18:21:08Z","abstract_excerpt":"In this paper a robust version of the classical Wald test statistics for linear hypothesis in the logistic regression model is introduced and its properties are explored. We study the problem under the assumption of random covariates although some ideas with non random covariates are also considered. The family of tests considered is based on the minimum density power divergence estimator instead of the maximum likelihood estimator and it is referred to as the Wald-type test statistic in the paper. We obtain the asymptotic distribution and also study the robustness properties of the Wald type "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.07452","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":"2026-05-17T23:46:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FztvQf64V1mDpstK0S7u2fE/n+PduQC3gXedUuYu/dSI1dJBqUJACiSDxj8T7KBtGxXlkuaoeIEoj7mnCAdvBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T05:35:54.523065Z"},"content_sha256":"56de59bf32bdc8f89c3ecf359f26d8c2ffb0e73673b217179e40f2a9af28a0ca","schema_version":"1.0","event_id":"sha256:56de59bf32bdc8f89c3ecf359f26d8c2ffb0e73673b217179e40f2a9af28a0ca"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FWDZHUZOWATK25J7TEWPDESDJG/bundle.json","state_url":"https://pith.science/pith/FWDZHUZOWATK25J7TEWPDESDJG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FWDZHUZOWATK25J7TEWPDESDJG/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":"2026-05-27T05:35:54Z","links":{"resolver":"https://pith.science/pith/FWDZHUZOWATK25J7TEWPDESDJG","bundle":"https://pith.science/pith/FWDZHUZOWATK25J7TEWPDESDJG/bundle.json","state":"https://pith.science/pith/FWDZHUZOWATK25J7TEWPDESDJG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FWDZHUZOWATK25J7TEWPDESDJG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:FWDZHUZOWATK25J7TEWPDESDJG","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":"03eddb84c8b28be293a29767f2ea30e9bc936cdf088c654e4a89669425820d82","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-09-23T18:21:08Z","title_canon_sha256":"78e0ae47a6c0335e54b6a6b7e28906e462e94a837ae82aaae42d34c90b50821c"},"schema_version":"1.0","source":{"id":"1609.07452","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1609.07452","created_at":"2026-05-17T23:46:46Z"},{"alias_kind":"arxiv_version","alias_value":"1609.07452v1","created_at":"2026-05-17T23:46:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.07452","created_at":"2026-05-17T23:46:46Z"},{"alias_kind":"pith_short_12","alias_value":"FWDZHUZOWATK","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_16","alias_value":"FWDZHUZOWATK25J7","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_8","alias_value":"FWDZHUZO","created_at":"2026-05-18T12:30:15Z"}],"graph_snapshots":[{"event_id":"sha256:56de59bf32bdc8f89c3ecf359f26d8c2ffb0e73673b217179e40f2a9af28a0ca","target":"graph","created_at":"2026-05-17T23:46:46Z","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":"In this paper a robust version of the classical Wald test statistics for linear hypothesis in the logistic regression model is introduced and its properties are explored. We study the problem under the assumption of random covariates although some ideas with non random covariates are also considered. The family of tests considered is based on the minimum density power divergence estimator instead of the maximum likelihood estimator and it is referred to as the Wald-type test statistic in the paper. We obtain the asymptotic distribution and also study the robustness properties of the Wald type ","authors_text":"Abhijit Mandal, Abhik Ghosh, Ayandrendanath Basu, Leandro Pardo, Nirian Martin","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-09-23T18:21:08Z","title":"A Wald-type test statistic for testing linear hypothesis in logistic regression models based on minimum density power divergence estimator"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.07452","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":"sha256:626e7bf283d8e7ed4807003137dbffbd957dec6388779b239086d4f2a239154a","target":"record","created_at":"2026-05-17T23:46:46Z","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":"03eddb84c8b28be293a29767f2ea30e9bc936cdf088c654e4a89669425820d82","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-09-23T18:21:08Z","title_canon_sha256":"78e0ae47a6c0335e54b6a6b7e28906e462e94a837ae82aaae42d34c90b50821c"},"schema_version":"1.0","source":{"id":"1609.07452","kind":"arxiv","version":1}},"canonical_sha256":"2d8793d32eb026ad753f992cf192434999719d8e80706461514e62ecf73688fb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2d8793d32eb026ad753f992cf192434999719d8e80706461514e62ecf73688fb","first_computed_at":"2026-05-17T23:46:46.646572Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:46:46.646572Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pGZW3X/ewge5BeyIMlyYl4cUM7rAChVgFCT6tyis6m1Pf5u3Ngn/Tkgr0PSPM5XtbVyV17ls1OVhaMogY17/Dg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:46:46.647135Z","signed_message":"canonical_sha256_bytes"},"source_id":"1609.07452","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:626e7bf283d8e7ed4807003137dbffbd957dec6388779b239086d4f2a239154a","sha256:56de59bf32bdc8f89c3ecf359f26d8c2ffb0e73673b217179e40f2a9af28a0ca"],"state_sha256":"1966cf86f1f2604d10dc25f63bc398e622c6322de5326ab1a49f7c68e9969159"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1IXNWx4cXHVEART08vk6iF1HibOGtpHqQTud0b4kg1qq5LTqr820biqLuY+tedX7gDS4Ct7in+caibMoPU7mDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T05:35:54.526133Z","bundle_sha256":"27df8cdd748882c365aeaaa96fd27c4523b280d40e5415291450fb64e3c725e9"}}