{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:5PUAJLK6OMOYV4IV3OYDTJQA2Z","short_pith_number":"pith:5PUAJLK6","canonical_record":{"source":{"id":"1607.00963","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-07-04T17:12:00Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"9a9246bcebbb8f6e725c75e720008a3f8931c719d6dd42101422c4a8a33670ba","abstract_canon_sha256":"8adbc136966c40546261e5b1f9f64f39605534646d419ca013474f568aff6d83"},"schema_version":"1.0"},"canonical_sha256":"ebe804ad5e731d8af115dbb039a600d65b817500721a93e3e20b4f39f83dcb75","source":{"kind":"arxiv","id":"1607.00963","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.00963","created_at":"2026-05-18T01:11:33Z"},{"alias_kind":"arxiv_version","alias_value":"1607.00963v1","created_at":"2026-05-18T01:11:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.00963","created_at":"2026-05-18T01:11:33Z"},{"alias_kind":"pith_short_12","alias_value":"5PUAJLK6OMOY","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_16","alias_value":"5PUAJLK6OMOYV4IV","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_8","alias_value":"5PUAJLK6","created_at":"2026-05-18T12:30:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:5PUAJLK6OMOYV4IV3OYDTJQA2Z","target":"record","payload":{"canonical_record":{"source":{"id":"1607.00963","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-07-04T17:12:00Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"9a9246bcebbb8f6e725c75e720008a3f8931c719d6dd42101422c4a8a33670ba","abstract_canon_sha256":"8adbc136966c40546261e5b1f9f64f39605534646d419ca013474f568aff6d83"},"schema_version":"1.0"},"canonical_sha256":"ebe804ad5e731d8af115dbb039a600d65b817500721a93e3e20b4f39f83dcb75","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:11:33.981989Z","signature_b64":"dJL7FaZwT3OwLcwy5HUY/2Uy5s0s/DATo78TLOevrs7XvAMgs2gQl5Nfx6aDmyJ4Ng1TNs4dAdUXdy1GjIy4Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ebe804ad5e731d8af115dbb039a600d65b817500721a93e3e20b4f39f83dcb75","last_reissued_at":"2026-05-18T01:11:33.981575Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:11:33.981575Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1607.00963","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":"2026-05-18T01:11:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1E4NWh1PDF/ZgbU403BzN+yg4NZTip74sw4Q4gwRf2veNwS8qseEp52vKddDm39CUnxTObO8iTDW2P7OXYHSAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T21:24:53.160205Z"},"content_sha256":"5bccdf6c1d8eb4a5de3394d6364329daa50dd66965d55bfb076f697098877a1a","schema_version":"1.0","event_id":"sha256:5bccdf6c1d8eb4a5de3394d6364329daa50dd66965d55bfb076f697098877a1a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:5PUAJLK6OMOYV4IV3OYDTJQA2Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimal bandwidth selection for semi-recursive kernel regression estimators","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Yousri Slaoui","submitted_at":"2016-07-04T17:12:00Z","abstract_excerpt":"In this paper we propose an automatic selection of the bandwidth of the semi-recursive kernel estimators of a regression function defined by the stochastic approximation algorithm. We showed that, using the selected bandwidth and some special stepsizes, the proposed semi-recursive estimators will be very competitive to the nonrecursive one in terms of estimation error but much better in terms of computational costs. We corroborated these theoretical results through simulation study and a real dataset."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.00963","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":"2026-05-18T01:11:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uPT2KlNLJKHPDnem9WeLEjb0Cd40/x8M0qrG7JRxEFweiipFeRnja0GRV3EdfBS/Qvr7/ogzdpxNiTaYJWq0BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T21:24:53.160555Z"},"content_sha256":"3e6cc2d1c01e465dfcef80198cefec7607661dde3eb72df0bf68ed5ed5df68b9","schema_version":"1.0","event_id":"sha256:3e6cc2d1c01e465dfcef80198cefec7607661dde3eb72df0bf68ed5ed5df68b9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5PUAJLK6OMOYV4IV3OYDTJQA2Z/bundle.json","state_url":"https://pith.science/pith/5PUAJLK6OMOYV4IV3OYDTJQA2Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5PUAJLK6OMOYV4IV3OYDTJQA2Z/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":"2026-06-27T21:24:53Z","links":{"resolver":"https://pith.science/pith/5PUAJLK6OMOYV4IV3OYDTJQA2Z","bundle":"https://pith.science/pith/5PUAJLK6OMOYV4IV3OYDTJQA2Z/bundle.json","state":"https://pith.science/pith/5PUAJLK6OMOYV4IV3OYDTJQA2Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5PUAJLK6OMOYV4IV3OYDTJQA2Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:5PUAJLK6OMOYV4IV3OYDTJQA2Z","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":"8adbc136966c40546261e5b1f9f64f39605534646d419ca013474f568aff6d83","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-07-04T17:12:00Z","title_canon_sha256":"9a9246bcebbb8f6e725c75e720008a3f8931c719d6dd42101422c4a8a33670ba"},"schema_version":"1.0","source":{"id":"1607.00963","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.00963","created_at":"2026-05-18T01:11:33Z"},{"alias_kind":"arxiv_version","alias_value":"1607.00963v1","created_at":"2026-05-18T01:11:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.00963","created_at":"2026-05-18T01:11:33Z"},{"alias_kind":"pith_short_12","alias_value":"5PUAJLK6OMOY","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_16","alias_value":"5PUAJLK6OMOYV4IV","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_8","alias_value":"5PUAJLK6","created_at":"2026-05-18T12:30:01Z"}],"graph_snapshots":[{"event_id":"sha256:3e6cc2d1c01e465dfcef80198cefec7607661dde3eb72df0bf68ed5ed5df68b9","target":"graph","created_at":"2026-05-18T01:11:33Z","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 we propose an automatic selection of the bandwidth of the semi-recursive kernel estimators of a regression function defined by the stochastic approximation algorithm. We showed that, using the selected bandwidth and some special stepsizes, the proposed semi-recursive estimators will be very competitive to the nonrecursive one in terms of estimation error but much better in terms of computational costs. We corroborated these theoretical results through simulation study and a real dataset.","authors_text":"Yousri Slaoui","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-07-04T17:12:00Z","title":"Optimal bandwidth selection for semi-recursive kernel regression estimators"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.00963","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":"sha256:5bccdf6c1d8eb4a5de3394d6364329daa50dd66965d55bfb076f697098877a1a","target":"record","created_at":"2026-05-18T01:11:33Z","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":"8adbc136966c40546261e5b1f9f64f39605534646d419ca013474f568aff6d83","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-07-04T17:12:00Z","title_canon_sha256":"9a9246bcebbb8f6e725c75e720008a3f8931c719d6dd42101422c4a8a33670ba"},"schema_version":"1.0","source":{"id":"1607.00963","kind":"arxiv","version":1}},"canonical_sha256":"ebe804ad5e731d8af115dbb039a600d65b817500721a93e3e20b4f39f83dcb75","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ebe804ad5e731d8af115dbb039a600d65b817500721a93e3e20b4f39f83dcb75","first_computed_at":"2026-05-18T01:11:33.981575Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:11:33.981575Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dJL7FaZwT3OwLcwy5HUY/2Uy5s0s/DATo78TLOevrs7XvAMgs2gQl5Nfx6aDmyJ4Ng1TNs4dAdUXdy1GjIy4Ag==","signature_status":"signed_v1","signed_at":"2026-05-18T01:11:33.981989Z","signed_message":"canonical_sha256_bytes"},"source_id":"1607.00963","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5bccdf6c1d8eb4a5de3394d6364329daa50dd66965d55bfb076f697098877a1a","sha256:3e6cc2d1c01e465dfcef80198cefec7607661dde3eb72df0bf68ed5ed5df68b9"],"state_sha256":"adbb93b77b9c53de663b60041d03f967c474f2a2b0ddb06194f66dd3cbc5a792"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sqUoHWl8njW2h6y6XYuOI0CZpEbVdl4hNOVGB/4vUokgfxXyM05dzSCK2hWzI6ZESPGAy5nFFj+uIKJ2gwv6AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T21:24:53.162501Z","bundle_sha256":"eb70ad24f7e2c7711a36e865dd5fc131e94d3b138d9dcaf786253e5b9a07db60"}}