{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:CI2CQIYPFSAPIA35ADMPDTTC2W","short_pith_number":"pith:CI2CQIYP","canonical_record":{"source":{"id":"1811.09016","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-22T04:07:14Z","cross_cats_sorted":["stat.AP","stat.TH"],"title_canon_sha256":"5264cf259e04e11248cdec43b99cb1670f3094fa07eeafe9010cab84007ba283","abstract_canon_sha256":"9126399b8a98b119687b4e1dad2ac19e37d39fa1455fffa116527cc18c7de152"},"schema_version":"1.0"},"canonical_sha256":"123428230f2c80f4037d00d8f1ce62d5b5793b2c72c016e850df86804c316c35","source":{"kind":"arxiv","id":"1811.09016","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.09016","created_at":"2026-05-18T00:00:07Z"},{"alias_kind":"arxiv_version","alias_value":"1811.09016v1","created_at":"2026-05-18T00:00:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.09016","created_at":"2026-05-18T00:00:07Z"},{"alias_kind":"pith_short_12","alias_value":"CI2CQIYPFSAP","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"CI2CQIYPFSAPIA35","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"CI2CQIYP","created_at":"2026-05-18T12:32:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:CI2CQIYPFSAPIA35ADMPDTTC2W","target":"record","payload":{"canonical_record":{"source":{"id":"1811.09016","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-22T04:07:14Z","cross_cats_sorted":["stat.AP","stat.TH"],"title_canon_sha256":"5264cf259e04e11248cdec43b99cb1670f3094fa07eeafe9010cab84007ba283","abstract_canon_sha256":"9126399b8a98b119687b4e1dad2ac19e37d39fa1455fffa116527cc18c7de152"},"schema_version":"1.0"},"canonical_sha256":"123428230f2c80f4037d00d8f1ce62d5b5793b2c72c016e850df86804c316c35","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:07.285823Z","signature_b64":"V5Y82FOT1lQs14G5cY/jzzQDW0bWO5nt01Fkwe297gSoOKcqnafyCc2g7THDqOXZW9YMQ2EG7hi9UwJblEBnDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"123428230f2c80f4037d00d8f1ce62d5b5793b2c72c016e850df86804c316c35","last_reissued_at":"2026-05-18T00:00:07.285100Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:07.285100Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.09016","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":"2026-05-18T00:00:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fxcFlh7yadwIDTfqDGWnkBvzJZyEnlLXQH4ClGRzS8UBX/SI0BEKJP7dyuAfC7CNVw3tKRn52Bt2R6cyY0WrAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T01:47:35.539230Z"},"content_sha256":"3d706fa893e6fe6b229fe83bd8bea4686718178de06fc972f87a9412ddcc6f55","schema_version":"1.0","event_id":"sha256:3d706fa893e6fe6b229fe83bd8bea4686718178de06fc972f87a9412ddcc6f55"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:CI2CQIYPFSAPIA35ADMPDTTC2W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Penalized least squares approximation methods and their applications to stochastic processes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP","stat.TH"],"primary_cat":"math.ST","authors_text":"nakahiro yoshida, Takumi Suzuki","submitted_at":"2018-11-22T04:07:14Z","abstract_excerpt":"We construct an objective function that consists of a quadratic approximation term and a penalty term. Thanks to the quadratic approximation, we can deal with various kinds of loss functions into a unified way, and by taking advantage of the penalty term, we can simultaneously execute variable selection and parameter estimation. In this article, we show that our estimator has oracle properties, and even better property. We also treat an stochastic processes as applications."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.09016","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":"2026-05-18T00:00:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p6nYax/TrfNJSoR5LZBASMHhlB6yAmYoYq8CaCE8ICZpz5+nNAjdBt1R3CRepa3h+UBicVt0AsFx8jZQiXhgBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T01:47:35.539950Z"},"content_sha256":"e13721f9f701686300e418f0d8ca32f563d99e318fb8c12893a2d8ced688219f","schema_version":"1.0","event_id":"sha256:e13721f9f701686300e418f0d8ca32f563d99e318fb8c12893a2d8ced688219f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CI2CQIYPFSAPIA35ADMPDTTC2W/bundle.json","state_url":"https://pith.science/pith/CI2CQIYPFSAPIA35ADMPDTTC2W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CI2CQIYPFSAPIA35ADMPDTTC2W/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":"2026-06-09T01:47:35Z","links":{"resolver":"https://pith.science/pith/CI2CQIYPFSAPIA35ADMPDTTC2W","bundle":"https://pith.science/pith/CI2CQIYPFSAPIA35ADMPDTTC2W/bundle.json","state":"https://pith.science/pith/CI2CQIYPFSAPIA35ADMPDTTC2W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CI2CQIYPFSAPIA35ADMPDTTC2W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:CI2CQIYPFSAPIA35ADMPDTTC2W","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":"9126399b8a98b119687b4e1dad2ac19e37d39fa1455fffa116527cc18c7de152","cross_cats_sorted":["stat.AP","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-22T04:07:14Z","title_canon_sha256":"5264cf259e04e11248cdec43b99cb1670f3094fa07eeafe9010cab84007ba283"},"schema_version":"1.0","source":{"id":"1811.09016","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.09016","created_at":"2026-05-18T00:00:07Z"},{"alias_kind":"arxiv_version","alias_value":"1811.09016v1","created_at":"2026-05-18T00:00:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.09016","created_at":"2026-05-18T00:00:07Z"},{"alias_kind":"pith_short_12","alias_value":"CI2CQIYPFSAP","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"CI2CQIYPFSAPIA35","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"CI2CQIYP","created_at":"2026-05-18T12:32:16Z"}],"graph_snapshots":[{"event_id":"sha256:e13721f9f701686300e418f0d8ca32f563d99e318fb8c12893a2d8ced688219f","target":"graph","created_at":"2026-05-18T00:00:07Z","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 construct an objective function that consists of a quadratic approximation term and a penalty term. Thanks to the quadratic approximation, we can deal with various kinds of loss functions into a unified way, and by taking advantage of the penalty term, we can simultaneously execute variable selection and parameter estimation. In this article, we show that our estimator has oracle properties, and even better property. We also treat an stochastic processes as applications.","authors_text":"nakahiro yoshida, Takumi Suzuki","cross_cats":["stat.AP","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-22T04:07:14Z","title":"Penalized least squares approximation methods and their applications to stochastic processes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.09016","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":"sha256:3d706fa893e6fe6b229fe83bd8bea4686718178de06fc972f87a9412ddcc6f55","target":"record","created_at":"2026-05-18T00:00:07Z","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":"9126399b8a98b119687b4e1dad2ac19e37d39fa1455fffa116527cc18c7de152","cross_cats_sorted":["stat.AP","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-22T04:07:14Z","title_canon_sha256":"5264cf259e04e11248cdec43b99cb1670f3094fa07eeafe9010cab84007ba283"},"schema_version":"1.0","source":{"id":"1811.09016","kind":"arxiv","version":1}},"canonical_sha256":"123428230f2c80f4037d00d8f1ce62d5b5793b2c72c016e850df86804c316c35","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"123428230f2c80f4037d00d8f1ce62d5b5793b2c72c016e850df86804c316c35","first_computed_at":"2026-05-18T00:00:07.285100Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:00:07.285100Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"V5Y82FOT1lQs14G5cY/jzzQDW0bWO5nt01Fkwe297gSoOKcqnafyCc2g7THDqOXZW9YMQ2EG7hi9UwJblEBnDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:00:07.285823Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.09016","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3d706fa893e6fe6b229fe83bd8bea4686718178de06fc972f87a9412ddcc6f55","sha256:e13721f9f701686300e418f0d8ca32f563d99e318fb8c12893a2d8ced688219f"],"state_sha256":"e0f9ce1e5489b79c8d4b1ba7067713af6ad319beafae5a794f92b0c1dadc534b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NBRLhLW2inDnYYRM9Eh5XyOVbtgkayLT6IwHr94VJ3u2SPQV9llyVG6AkDA3GTnggNdj+NLDB4C55Lnm7PBxAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T01:47:35.545605Z","bundle_sha256":"b6f92a18af505ae5dd2ad904e36925c986f6c4035d370b8bfa8131b2aa8e6815"}}