{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2010:3W6WC3SCHSLM6AVB4JYWL73R2C","short_pith_number":"pith:3W6WC3SC","canonical_record":{"source":{"id":"1004.5199","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2010-04-29T06:41:46Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"fda477471ba3544bf8916ed36b725a0eebabe0b0d3ca3a112b015730864131f1","abstract_canon_sha256":"638187f0ffa685d490d68e5df989d4087c62743e8fc7460212c465ae02537cff"},"schema_version":"1.0"},"canonical_sha256":"ddbd616e423c96cf02a1e27165ff71d096abcfab1e6219a10c09b28b8902e58b","source":{"kind":"arxiv","id":"1004.5199","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1004.5199","created_at":"2026-05-18T04:36:18Z"},{"alias_kind":"arxiv_version","alias_value":"1004.5199v2","created_at":"2026-05-18T04:36:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1004.5199","created_at":"2026-05-18T04:36:18Z"},{"alias_kind":"pith_short_12","alias_value":"3W6WC3SCHSLM","created_at":"2026-05-18T12:26:03Z"},{"alias_kind":"pith_short_16","alias_value":"3W6WC3SCHSLM6AVB","created_at":"2026-05-18T12:26:03Z"},{"alias_kind":"pith_short_8","alias_value":"3W6WC3SC","created_at":"2026-05-18T12:26:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2010:3W6WC3SCHSLM6AVB4JYWL73R2C","target":"record","payload":{"canonical_record":{"source":{"id":"1004.5199","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2010-04-29T06:41:46Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"fda477471ba3544bf8916ed36b725a0eebabe0b0d3ca3a112b015730864131f1","abstract_canon_sha256":"638187f0ffa685d490d68e5df989d4087c62743e8fc7460212c465ae02537cff"},"schema_version":"1.0"},"canonical_sha256":"ddbd616e423c96cf02a1e27165ff71d096abcfab1e6219a10c09b28b8902e58b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:36:18.652807Z","signature_b64":"ylXP66xgQuu2K8ypCujJyTuL/XDE9WgJtLX/A+dD64j4psumJ/3Dm78dorDon1bg+rq0IsKfKCyZk0dKS4+wBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ddbd616e423c96cf02a1e27165ff71d096abcfab1e6219a10c09b28b8902e58b","last_reissued_at":"2026-05-18T04:36:18.652113Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:36:18.652113Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1004.5199","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T04:36:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"14ESGaHPmVJ/8ReZPpsweo+W5dPZpcxnV4KwAxq1UbubbxZer4MFDYFKW6/eSIE1Jj4hezbKajaR/NY5/uLyAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T19:15:34.108180Z"},"content_sha256":"5f9f300a47cdd909100ccdd7fc3350805efe8b3eb8fd187e8c472bcd9ef6220c","schema_version":"1.0","event_id":"sha256:5f9f300a47cdd909100ccdd7fc3350805efe8b3eb8fd187e8c472bcd9ef6220c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2010:3W6WC3SCHSLM6AVB4JYWL73R2C","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sequential adaptive estimators in nonparametric autoregressive models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Ouerdia Arkoun (LMRS)","submitted_at":"2010-04-29T06:41:46Z","abstract_excerpt":"We constuct a sequential adaptive procedure for estimating the autoregressive function at a given point in nonparametric autoregression models with Gaussian noise. We make use of the sequential kernel estimators. The optimal adaptive convergence rate is given as well as the upper bound for the minimax risk."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1004.5199","kind":"arxiv","version":2},"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":"2026-05-18T04:36:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6Mct1oz5PUTRPfXHEsPYMmcfCCLOldE/lFcsWjHaW6mfZeYLMxtjCRzPVbg+6rT0lAQOpgU/1Tfuc2JrhdI7Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T19:15:34.108544Z"},"content_sha256":"5a05a6b453f0e3e3012f570248d2e33a299432cf419a75e047951c7e37adf8b7","schema_version":"1.0","event_id":"sha256:5a05a6b453f0e3e3012f570248d2e33a299432cf419a75e047951c7e37adf8b7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3W6WC3SCHSLM6AVB4JYWL73R2C/bundle.json","state_url":"https://pith.science/pith/3W6WC3SCHSLM6AVB4JYWL73R2C/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3W6WC3SCHSLM6AVB4JYWL73R2C/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":"2026-06-27T19:15:34Z","links":{"resolver":"https://pith.science/pith/3W6WC3SCHSLM6AVB4JYWL73R2C","bundle":"https://pith.science/pith/3W6WC3SCHSLM6AVB4JYWL73R2C/bundle.json","state":"https://pith.science/pith/3W6WC3SCHSLM6AVB4JYWL73R2C/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3W6WC3SCHSLM6AVB4JYWL73R2C/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2010:3W6WC3SCHSLM6AVB4JYWL73R2C","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":"638187f0ffa685d490d68e5df989d4087c62743e8fc7460212c465ae02537cff","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2010-04-29T06:41:46Z","title_canon_sha256":"fda477471ba3544bf8916ed36b725a0eebabe0b0d3ca3a112b015730864131f1"},"schema_version":"1.0","source":{"id":"1004.5199","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1004.5199","created_at":"2026-05-18T04:36:18Z"},{"alias_kind":"arxiv_version","alias_value":"1004.5199v2","created_at":"2026-05-18T04:36:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1004.5199","created_at":"2026-05-18T04:36:18Z"},{"alias_kind":"pith_short_12","alias_value":"3W6WC3SCHSLM","created_at":"2026-05-18T12:26:03Z"},{"alias_kind":"pith_short_16","alias_value":"3W6WC3SCHSLM6AVB","created_at":"2026-05-18T12:26:03Z"},{"alias_kind":"pith_short_8","alias_value":"3W6WC3SC","created_at":"2026-05-18T12:26:03Z"}],"graph_snapshots":[{"event_id":"sha256:5a05a6b453f0e3e3012f570248d2e33a299432cf419a75e047951c7e37adf8b7","target":"graph","created_at":"2026-05-18T04:36:18Z","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":"We constuct a sequential adaptive procedure for estimating the autoregressive function at a given point in nonparametric autoregression models with Gaussian noise. We make use of the sequential kernel estimators. The optimal adaptive convergence rate is given as well as the upper bound for the minimax risk.","authors_text":"Ouerdia Arkoun (LMRS)","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2010-04-29T06:41:46Z","title":"Sequential adaptive estimators in nonparametric autoregressive models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1004.5199","kind":"arxiv","version":2},"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":"sha256:5f9f300a47cdd909100ccdd7fc3350805efe8b3eb8fd187e8c472bcd9ef6220c","target":"record","created_at":"2026-05-18T04:36:18Z","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":"638187f0ffa685d490d68e5df989d4087c62743e8fc7460212c465ae02537cff","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2010-04-29T06:41:46Z","title_canon_sha256":"fda477471ba3544bf8916ed36b725a0eebabe0b0d3ca3a112b015730864131f1"},"schema_version":"1.0","source":{"id":"1004.5199","kind":"arxiv","version":2}},"canonical_sha256":"ddbd616e423c96cf02a1e27165ff71d096abcfab1e6219a10c09b28b8902e58b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ddbd616e423c96cf02a1e27165ff71d096abcfab1e6219a10c09b28b8902e58b","first_computed_at":"2026-05-18T04:36:18.652113Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T04:36:18.652113Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ylXP66xgQuu2K8ypCujJyTuL/XDE9WgJtLX/A+dD64j4psumJ/3Dm78dorDon1bg+rq0IsKfKCyZk0dKS4+wBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T04:36:18.652807Z","signed_message":"canonical_sha256_bytes"},"source_id":"1004.5199","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5f9f300a47cdd909100ccdd7fc3350805efe8b3eb8fd187e8c472bcd9ef6220c","sha256:5a05a6b453f0e3e3012f570248d2e33a299432cf419a75e047951c7e37adf8b7"],"state_sha256":"c3f7489218f9ccebab04c99e61ca9b8b3c86bff3831f270d84de471bdbb75edf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wsGKFsi+cjElg2g1OPK2IqJ1cdezeromAjctlMK7aGLhVWkOweJCpRMd5vsIH5EIff8R85flrLxINIm3fXD0CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T19:15:34.110487Z","bundle_sha256":"4b284e847e9fa3714c02f87752bbfbd9c617d6630c04b0292e44947ff5ed5547"}}