{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:HSWK7DWVH7FTUCEE3GIP7Z4KGM","short_pith_number":"pith:HSWK7DWV","schema_version":"1.0","canonical_sha256":"3cacaf8ed53fcb3a0884d990ffe78a333b5aec43b8caa868b623f0878ba5545a","source":{"kind":"arxiv","id":"1303.4288","version":1},"attestation_state":"computed","paper":{"title":"Iterative Isotonic Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Arnaud Guyader, Eric Matzner-L{\\o}ber, Nick Hengartner, Nicolas J\\'egou","submitted_at":"2013-03-18T15:31:32Z","abstract_excerpt":"This article introduces a new nonparametric method for estimating a univariate regression function of bounded variation. The method exploits the Jordan decomposition which states that a function of bounded variation can be decomposed as the sum of a non-decreasing function and a non-increasing function. This suggests combining the backfitting algorithm for estimating additive functions with isotonic regression for estimating monotone functions. The resulting iterative algorithm is called Iterative Isotonic Regression (I.I.R.). The main technical result in this paper is the consistency of the p"},"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":"1303.4288","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2013-03-18T15:31:32Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"d6f8465b747fe989a2faac2b519ad0050aca67b794435b720ae19f86f4d76cc5","abstract_canon_sha256":"c40b6fd1f5b8783942760c4de2f23c16ce84450d8355fe9c9779fd4787242972"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:09:33.069092Z","signature_b64":"PzW4g/xMVuPOWbdZfbWR5PX7E4WmPmwnY25IQci8tFlFIEws94xz67qDgL2fsmiEHxV5bzPGujMrWnfLJsVaAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3cacaf8ed53fcb3a0884d990ffe78a333b5aec43b8caa868b623f0878ba5545a","last_reissued_at":"2026-05-18T01:09:33.068577Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:09:33.068577Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Iterative Isotonic Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Arnaud Guyader, Eric Matzner-L{\\o}ber, Nick Hengartner, Nicolas J\\'egou","submitted_at":"2013-03-18T15:31:32Z","abstract_excerpt":"This article introduces a new nonparametric method for estimating a univariate regression function of bounded variation. The method exploits the Jordan decomposition which states that a function of bounded variation can be decomposed as the sum of a non-decreasing function and a non-increasing function. This suggests combining the backfitting algorithm for estimating additive functions with isotonic regression for estimating monotone functions. The resulting iterative algorithm is called Iterative Isotonic Regression (I.I.R.). The main technical result in this paper is the consistency of the p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1303.4288","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":"1303.4288","created_at":"2026-05-18T01:09:33.068640+00:00"},{"alias_kind":"arxiv_version","alias_value":"1303.4288v1","created_at":"2026-05-18T01:09:33.068640+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1303.4288","created_at":"2026-05-18T01:09:33.068640+00:00"},{"alias_kind":"pith_short_12","alias_value":"HSWK7DWVH7FT","created_at":"2026-05-18T12:27:46.883200+00:00"},{"alias_kind":"pith_short_16","alias_value":"HSWK7DWVH7FTUCEE","created_at":"2026-05-18T12:27:46.883200+00:00"},{"alias_kind":"pith_short_8","alias_value":"HSWK7DWV","created_at":"2026-05-18T12:27:46.883200+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/HSWK7DWVH7FTUCEE3GIP7Z4KGM","json":"https://pith.science/pith/HSWK7DWVH7FTUCEE3GIP7Z4KGM.json","graph_json":"https://pith.science/api/pith-number/HSWK7DWVH7FTUCEE3GIP7Z4KGM/graph.json","events_json":"https://pith.science/api/pith-number/HSWK7DWVH7FTUCEE3GIP7Z4KGM/events.json","paper":"https://pith.science/paper/HSWK7DWV"},"agent_actions":{"view_html":"https://pith.science/pith/HSWK7DWVH7FTUCEE3GIP7Z4KGM","download_json":"https://pith.science/pith/HSWK7DWVH7FTUCEE3GIP7Z4KGM.json","view_paper":"https://pith.science/paper/HSWK7DWV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1303.4288&json=true","fetch_graph":"https://pith.science/api/pith-number/HSWK7DWVH7FTUCEE3GIP7Z4KGM/graph.json","fetch_events":"https://pith.science/api/pith-number/HSWK7DWVH7FTUCEE3GIP7Z4KGM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HSWK7DWVH7FTUCEE3GIP7Z4KGM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HSWK7DWVH7FTUCEE3GIP7Z4KGM/action/storage_attestation","attest_author":"https://pith.science/pith/HSWK7DWVH7FTUCEE3GIP7Z4KGM/action/author_attestation","sign_citation":"https://pith.science/pith/HSWK7DWVH7FTUCEE3GIP7Z4KGM/action/citation_signature","submit_replication":"https://pith.science/pith/HSWK7DWVH7FTUCEE3GIP7Z4KGM/action/replication_record"}},"created_at":"2026-05-18T01:09:33.068640+00:00","updated_at":"2026-05-18T01:09:33.068640+00:00"}