{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:Q4EEDSDYPJ24SCXTFL3ESSYYEN","short_pith_number":"pith:Q4EEDSDY","canonical_record":{"source":{"id":"1602.00886","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-02T11:27:26Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"2bc5298ed0e4948196ae24d19f1f64419991b673438227a563a45d2552cf43f2","abstract_canon_sha256":"6c20937a5bdf77380cc948af24e2379afaf72ca8d793b3f7c8256b25753d1f4c"},"schema_version":"1.0"},"canonical_sha256":"870841c8787a75c90af32af6494b18234b1bc5b143dc13fd16103b333b9f3f74","source":{"kind":"arxiv","id":"1602.00886","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.00886","created_at":"2026-05-18T01:21:24Z"},{"alias_kind":"arxiv_version","alias_value":"1602.00886v1","created_at":"2026-05-18T01:21:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.00886","created_at":"2026-05-18T01:21:24Z"},{"alias_kind":"pith_short_12","alias_value":"Q4EEDSDYPJ24","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_16","alias_value":"Q4EEDSDYPJ24SCXT","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_8","alias_value":"Q4EEDSDY","created_at":"2026-05-18T12:30:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:Q4EEDSDYPJ24SCXTFL3ESSYYEN","target":"record","payload":{"canonical_record":{"source":{"id":"1602.00886","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-02T11:27:26Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"2bc5298ed0e4948196ae24d19f1f64419991b673438227a563a45d2552cf43f2","abstract_canon_sha256":"6c20937a5bdf77380cc948af24e2379afaf72ca8d793b3f7c8256b25753d1f4c"},"schema_version":"1.0"},"canonical_sha256":"870841c8787a75c90af32af6494b18234b1bc5b143dc13fd16103b333b9f3f74","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:21:24.386445Z","signature_b64":"pXcVEIPflBHqw6pvMmWHcFjPCULUdxLOnBNhK7khxiQW+9UAvz9948i5gUr0QDJ3yXH3yDnGEoAuRYEgnH7gBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"870841c8787a75c90af32af6494b18234b1bc5b143dc13fd16103b333b9f3f74","last_reissued_at":"2026-05-18T01:21:24.385745Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:21:24.385745Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1602.00886","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":"2026-05-18T01:21:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PGucaRi1zzqKGmw4scol9jvz/s9Xe5okYNhePEb27dy2NW6euoUL1XNvywMmWLLi2IBiIQvJEi/MTMP3LxtiBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T23:05:34.865716Z"},"content_sha256":"b1c31c927a74273ba43c189623113ff7346ecc5550559328fee297adba61c9de","schema_version":"1.0","event_id":"sha256:b1c31c927a74273ba43c189623113ff7346ecc5550559328fee297adba61c9de"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:Q4EEDSDYPJ24SCXTFL3ESSYYEN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Analysis of the Forward Search using some new results for martingales and empirical processes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Bent Nielsen, S{\\o}ren Johansen","submitted_at":"2016-02-02T11:27:26Z","abstract_excerpt":"The Forward Search is an iterative algorithm for avoiding outliers in a regression analysis suggested by Hadi and Simonoff (J. Amer. Statist. Assoc. 88 (1993) 1264-1272), see also Atkinson and Riani (Robust Diagnostic Regression Analysis (2000) Springer). The algorithm constructs subsets of \"good\" observations so that the size of the subsets increases as the algorithm progresses. It results in a sequence of regression estimators and forward residuals. Outliers are detected by monitoring the sequence of forward residuals. We show that the sequences of regression estimators and forward residuals"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.00886","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":"2026-05-18T01:21:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uMvqfwjJuA+ttqeGZayhym8dmDobqdqUh0einznxXa3sT5Is9vJVn2I8AWwl+YSa29dWyGQyfh8uZJAJp7guBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T23:05:34.866266Z"},"content_sha256":"b916b1b6004b501915c72b91961c837d23cd6b578f9473d8b19ef48ef3f642e3","schema_version":"1.0","event_id":"sha256:b916b1b6004b501915c72b91961c837d23cd6b578f9473d8b19ef48ef3f642e3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q4EEDSDYPJ24SCXTFL3ESSYYEN/bundle.json","state_url":"https://pith.science/pith/Q4EEDSDYPJ24SCXTFL3ESSYYEN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q4EEDSDYPJ24SCXTFL3ESSYYEN/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":"2026-06-06T23:05:34Z","links":{"resolver":"https://pith.science/pith/Q4EEDSDYPJ24SCXTFL3ESSYYEN","bundle":"https://pith.science/pith/Q4EEDSDYPJ24SCXTFL3ESSYYEN/bundle.json","state":"https://pith.science/pith/Q4EEDSDYPJ24SCXTFL3ESSYYEN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q4EEDSDYPJ24SCXTFL3ESSYYEN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:Q4EEDSDYPJ24SCXTFL3ESSYYEN","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":"6c20937a5bdf77380cc948af24e2379afaf72ca8d793b3f7c8256b25753d1f4c","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-02T11:27:26Z","title_canon_sha256":"2bc5298ed0e4948196ae24d19f1f64419991b673438227a563a45d2552cf43f2"},"schema_version":"1.0","source":{"id":"1602.00886","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.00886","created_at":"2026-05-18T01:21:24Z"},{"alias_kind":"arxiv_version","alias_value":"1602.00886v1","created_at":"2026-05-18T01:21:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.00886","created_at":"2026-05-18T01:21:24Z"},{"alias_kind":"pith_short_12","alias_value":"Q4EEDSDYPJ24","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_16","alias_value":"Q4EEDSDYPJ24SCXT","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_8","alias_value":"Q4EEDSDY","created_at":"2026-05-18T12:30:39Z"}],"graph_snapshots":[{"event_id":"sha256:b916b1b6004b501915c72b91961c837d23cd6b578f9473d8b19ef48ef3f642e3","target":"graph","created_at":"2026-05-18T01:21:24Z","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":"The Forward Search is an iterative algorithm for avoiding outliers in a regression analysis suggested by Hadi and Simonoff (J. Amer. Statist. Assoc. 88 (1993) 1264-1272), see also Atkinson and Riani (Robust Diagnostic Regression Analysis (2000) Springer). The algorithm constructs subsets of \"good\" observations so that the size of the subsets increases as the algorithm progresses. It results in a sequence of regression estimators and forward residuals. Outliers are detected by monitoring the sequence of forward residuals. We show that the sequences of regression estimators and forward residuals","authors_text":"Bent Nielsen, S{\\o}ren Johansen","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-02T11:27:26Z","title":"Analysis of the Forward Search using some new results for martingales and empirical processes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.00886","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:b1c31c927a74273ba43c189623113ff7346ecc5550559328fee297adba61c9de","target":"record","created_at":"2026-05-18T01:21:24Z","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":"6c20937a5bdf77380cc948af24e2379afaf72ca8d793b3f7c8256b25753d1f4c","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-02T11:27:26Z","title_canon_sha256":"2bc5298ed0e4948196ae24d19f1f64419991b673438227a563a45d2552cf43f2"},"schema_version":"1.0","source":{"id":"1602.00886","kind":"arxiv","version":1}},"canonical_sha256":"870841c8787a75c90af32af6494b18234b1bc5b143dc13fd16103b333b9f3f74","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"870841c8787a75c90af32af6494b18234b1bc5b143dc13fd16103b333b9f3f74","first_computed_at":"2026-05-18T01:21:24.385745Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:21:24.385745Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pXcVEIPflBHqw6pvMmWHcFjPCULUdxLOnBNhK7khxiQW+9UAvz9948i5gUr0QDJ3yXH3yDnGEoAuRYEgnH7gBg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:21:24.386445Z","signed_message":"canonical_sha256_bytes"},"source_id":"1602.00886","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b1c31c927a74273ba43c189623113ff7346ecc5550559328fee297adba61c9de","sha256:b916b1b6004b501915c72b91961c837d23cd6b578f9473d8b19ef48ef3f642e3"],"state_sha256":"782da00919b3eab7234e44a115034b85131033bc6d62c99ca6b1732203b0ac2a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NmkBkzTVG9lWJlBOvVD9fFYP0fF3T8XQh2UVh8c+hb28jj/RgKCW5kYBvm0kQplbunzibVSo1zoyY3wM6q1kBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T23:05:34.869547Z","bundle_sha256":"9dec4bd40e7e9fda20c7816d5481a0e9838a182c756b88e3df163eb63a4008cc"}}