{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:LB2N2UIQ4DS3MOMZKFOTNAUWBX","short_pith_number":"pith:LB2N2UIQ","canonical_record":{"source":{"id":"1603.03934","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-03-12T15:53:08Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"e47aa94d94d995f768b06a6928a4d5998b1514b6199d82b6e2300a32c6980172","abstract_canon_sha256":"5dbfe2fe46a6a484efd43274647112eda79800d5ecbdb384495edd285573e707"},"schema_version":"1.0"},"canonical_sha256":"5874dd5110e0e5b63999515d3682960de49175f20be2c1be3fb8f72179fa3eca","source":{"kind":"arxiv","id":"1603.03934","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1603.03934","created_at":"2026-05-18T01:19:09Z"},{"alias_kind":"arxiv_version","alias_value":"1603.03934v1","created_at":"2026-05-18T01:19:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.03934","created_at":"2026-05-18T01:19:09Z"},{"alias_kind":"pith_short_12","alias_value":"LB2N2UIQ4DS3","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_16","alias_value":"LB2N2UIQ4DS3MOMZ","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_8","alias_value":"LB2N2UIQ","created_at":"2026-05-18T12:30:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:LB2N2UIQ4DS3MOMZKFOTNAUWBX","target":"record","payload":{"canonical_record":{"source":{"id":"1603.03934","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-03-12T15:53:08Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"e47aa94d94d995f768b06a6928a4d5998b1514b6199d82b6e2300a32c6980172","abstract_canon_sha256":"5dbfe2fe46a6a484efd43274647112eda79800d5ecbdb384495edd285573e707"},"schema_version":"1.0"},"canonical_sha256":"5874dd5110e0e5b63999515d3682960de49175f20be2c1be3fb8f72179fa3eca","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:19:09.962255Z","signature_b64":"KFpQIkMgG5WvuLGcWNPhzEa6vHx0CcZ58xkhaH6Qba6pJEVNzxekObuMm/wXn1Hbf2kzVh/K/SMLfpVVu7voDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5874dd5110e0e5b63999515d3682960de49175f20be2c1be3fb8f72179fa3eca","last_reissued_at":"2026-05-18T01:19:09.961300Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:19:09.961300Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1603.03934","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":"2026-05-18T01:19:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CIEY24v4QGfyig6FBeIG27JLI+qj8BXGTOoMCcM10qK+YSGxsB85dK2P+Qgoy8EHibvKKsPyh7+33C/my94hDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T05:39:56.839174Z"},"content_sha256":"e458657405f7d507ec9dcc961c6104559cb1905803a77c2057d9715385c82293","schema_version":"1.0","event_id":"sha256:e458657405f7d507ec9dcc961c6104559cb1905803a77c2057d9715385c82293"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:LB2N2UIQ4DS3MOMZKFOTNAUWBX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Some new ideas in nonparametric estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Oleg Lepski","submitted_at":"2016-03-12T15:53:08Z","abstract_excerpt":"In the framework of an abstract statistical model we discuss how to use the solution of one estimation problem ({\\it Problem A}) in order to construct an estimator in another, completely different, {\\it Problem B}. As a solution of {\\it Problem A} we understand a data-driven selection from a given family of estimators $\\mathbf{A}(\\mH)=\\big\\{\\widehat{A}_\\mh, \\mh\\in\\mH\\big\\}$ and establishing for the selected estimator so-called oracle inequality. %parameterized by some se t$\\mH$. If $\\hat{\\mh}\\in\\mH$ is the selected parameter and $\\mathbf{B}(\\mH)=\\big\\{\\widehat{B}_\\mh, \\mh\\in\\mH\\big\\}$ is an es"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.03934","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":"2026-05-18T01:19:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QBrvrGy6wcyDmifIqOPgFw6gCtSzNJJgW6V7M4cenxq8kM2kKDX2C+EzxzA+cABt+IkY+th7Zgm1+Gnmj4EvDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T05:39:56.839542Z"},"content_sha256":"442a17747cbccd5f826e2873fffc500e41a093c71e2473b2192d6e7c4f9361d4","schema_version":"1.0","event_id":"sha256:442a17747cbccd5f826e2873fffc500e41a093c71e2473b2192d6e7c4f9361d4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LB2N2UIQ4DS3MOMZKFOTNAUWBX/bundle.json","state_url":"https://pith.science/pith/LB2N2UIQ4DS3MOMZKFOTNAUWBX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LB2N2UIQ4DS3MOMZKFOTNAUWBX/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":"2026-06-25T05:39:56Z","links":{"resolver":"https://pith.science/pith/LB2N2UIQ4DS3MOMZKFOTNAUWBX","bundle":"https://pith.science/pith/LB2N2UIQ4DS3MOMZKFOTNAUWBX/bundle.json","state":"https://pith.science/pith/LB2N2UIQ4DS3MOMZKFOTNAUWBX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LB2N2UIQ4DS3MOMZKFOTNAUWBX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:LB2N2UIQ4DS3MOMZKFOTNAUWBX","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":"5dbfe2fe46a6a484efd43274647112eda79800d5ecbdb384495edd285573e707","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-03-12T15:53:08Z","title_canon_sha256":"e47aa94d94d995f768b06a6928a4d5998b1514b6199d82b6e2300a32c6980172"},"schema_version":"1.0","source":{"id":"1603.03934","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1603.03934","created_at":"2026-05-18T01:19:09Z"},{"alias_kind":"arxiv_version","alias_value":"1603.03934v1","created_at":"2026-05-18T01:19:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.03934","created_at":"2026-05-18T01:19:09Z"},{"alias_kind":"pith_short_12","alias_value":"LB2N2UIQ4DS3","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_16","alias_value":"LB2N2UIQ4DS3MOMZ","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_8","alias_value":"LB2N2UIQ","created_at":"2026-05-18T12:30:29Z"}],"graph_snapshots":[{"event_id":"sha256:442a17747cbccd5f826e2873fffc500e41a093c71e2473b2192d6e7c4f9361d4","target":"graph","created_at":"2026-05-18T01:19:09Z","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 the framework of an abstract statistical model we discuss how to use the solution of one estimation problem ({\\it Problem A}) in order to construct an estimator in another, completely different, {\\it Problem B}. As a solution of {\\it Problem A} we understand a data-driven selection from a given family of estimators $\\mathbf{A}(\\mH)=\\big\\{\\widehat{A}_\\mh, \\mh\\in\\mH\\big\\}$ and establishing for the selected estimator so-called oracle inequality. %parameterized by some se t$\\mH$. If $\\hat{\\mh}\\in\\mH$ is the selected parameter and $\\mathbf{B}(\\mH)=\\big\\{\\widehat{B}_\\mh, \\mh\\in\\mH\\big\\}$ is an es","authors_text":"Oleg Lepski","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-03-12T15:53:08Z","title":"Some new ideas in nonparametric estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.03934","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:e458657405f7d507ec9dcc961c6104559cb1905803a77c2057d9715385c82293","target":"record","created_at":"2026-05-18T01:19:09Z","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":"5dbfe2fe46a6a484efd43274647112eda79800d5ecbdb384495edd285573e707","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-03-12T15:53:08Z","title_canon_sha256":"e47aa94d94d995f768b06a6928a4d5998b1514b6199d82b6e2300a32c6980172"},"schema_version":"1.0","source":{"id":"1603.03934","kind":"arxiv","version":1}},"canonical_sha256":"5874dd5110e0e5b63999515d3682960de49175f20be2c1be3fb8f72179fa3eca","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5874dd5110e0e5b63999515d3682960de49175f20be2c1be3fb8f72179fa3eca","first_computed_at":"2026-05-18T01:19:09.961300Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:19:09.961300Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KFpQIkMgG5WvuLGcWNPhzEa6vHx0CcZ58xkhaH6Qba6pJEVNzxekObuMm/wXn1Hbf2kzVh/K/SMLfpVVu7voDw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:19:09.962255Z","signed_message":"canonical_sha256_bytes"},"source_id":"1603.03934","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e458657405f7d507ec9dcc961c6104559cb1905803a77c2057d9715385c82293","sha256:442a17747cbccd5f826e2873fffc500e41a093c71e2473b2192d6e7c4f9361d4"],"state_sha256":"deba6987346c7b6c54d16f69b8260fd3637cc10d1b0a6aec9a8169ba8d3febd4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lPQvumz47Fw2xKOpkOfl+nltXR1HCD3RAyuPVCIaIbR06i3tgfVdGS7MP72nGRGApkYosPCXaJMp7z03e9ZjDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-25T05:39:56.841609Z","bundle_sha256":"8ddcc3fcc711a8f0bcec767d057a286f59804204fa8c18d722e705b3248724bf"}}