{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2007:MLKWF7V7KLZES5QW4CVYLA3R2B","short_pith_number":"pith:MLKWF7V7","canonical_record":{"source":{"id":"0708.0169","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2007-08-01T14:54:16Z","cross_cats_sorted":["math.PR","stat.ME","stat.TH"],"title_canon_sha256":"e6eb14212a2666ad7f259e6dc969ff10ae0c8f10c4d53c302838f86cba7e69eb","abstract_canon_sha256":"cab568fd32d202a62000dea92a4f8bdb29f486c1cbfc7b928faec3797f09f5cb"},"schema_version":"1.0"},"canonical_sha256":"62d562febf52f2497616e0ab858371d06fe37685702130c492aadd119d1326f2","source":{"kind":"arxiv","id":"0708.0169","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"0708.0169","created_at":"2026-05-18T00:34:39Z"},{"alias_kind":"arxiv_version","alias_value":"0708.0169v4","created_at":"2026-05-18T00:34:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.0708.0169","created_at":"2026-05-18T00:34:39Z"},{"alias_kind":"pith_short_12","alias_value":"MLKWF7V7KLZE","created_at":"2026-05-18T12:25:55Z"},{"alias_kind":"pith_short_16","alias_value":"MLKWF7V7KLZES5QW","created_at":"2026-05-18T12:25:55Z"},{"alias_kind":"pith_short_8","alias_value":"MLKWF7V7","created_at":"2026-05-18T12:25:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2007:MLKWF7V7KLZES5QW4CVYLA3R2B","target":"record","payload":{"canonical_record":{"source":{"id":"0708.0169","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2007-08-01T14:54:16Z","cross_cats_sorted":["math.PR","stat.ME","stat.TH"],"title_canon_sha256":"e6eb14212a2666ad7f259e6dc969ff10ae0c8f10c4d53c302838f86cba7e69eb","abstract_canon_sha256":"cab568fd32d202a62000dea92a4f8bdb29f486c1cbfc7b928faec3797f09f5cb"},"schema_version":"1.0"},"canonical_sha256":"62d562febf52f2497616e0ab858371d06fe37685702130c492aadd119d1326f2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:34:39.744057Z","signature_b64":"1DNj/Zqt2gfdf5RbyPH8fPlJllg2HTejuHaUjIz4FAZ03L8eWitfVk3MUx0MV7bhaaVOwcB05xNAKNzqUhg6Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"62d562febf52f2497616e0ab858371d06fe37685702130c492aadd119d1326f2","last_reissued_at":"2026-05-18T00:34:39.743294Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:34:39.743294Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"0708.0169","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:34:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0k7lAc/F83TVvyUSJRq9DyORzwoE48To7jCgr4WEDVtoV73ZRt6OfpT144dRTR/bhrf3YAzu8vEHnkqrfqcPCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T03:58:19.255126Z"},"content_sha256":"c4dc170fe6c9a643b3e6c0caced9ce4f2769cae11e509924a54b092ede06831f","schema_version":"1.0","event_id":"sha256:c4dc170fe6c9a643b3e6c0caced9ce4f2769cae11e509924a54b092ede06831f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2007:MLKWF7V7KLZES5QW4CVYLA3R2B","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Data-driven goodness-of-fit tests","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.PR","stat.ME","stat.TH"],"primary_cat":"math.ST","authors_text":"Mikhail Langovoy","submitted_at":"2007-08-01T14:54:16Z","abstract_excerpt":"We propose and study a general method for construction of consistent statistical tests on the basis of possibly indirect, corrupted, or partially available observations. The class of tests devised in the paper contains Neyman's smooth tests, data-driven score tests, and some types of multi-sample tests as basic examples. Our tests are data-driven and are additionally incorporated with model selection rules. The method allows to use a wide class of model selection rules that are based on the penalization idea. In particular, many of the optimal penalties, derived in statistical literature, can "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"0708.0169","kind":"arxiv","version":4},"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":"2026-05-18T00:34:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"INwpglNdYSHT46fx1BlVT5dSpPdq0rifDqbZdnovj+Ywnf0GOPc8KwaBLanxWG435ThE9c54MUYv0QJ8S+MrDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T03:58:19.255788Z"},"content_sha256":"2fd3659f0e3f4581d43077ebc0d9d5b908462a4a366292e9cca6fd306319ce66","schema_version":"1.0","event_id":"sha256:2fd3659f0e3f4581d43077ebc0d9d5b908462a4a366292e9cca6fd306319ce66"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MLKWF7V7KLZES5QW4CVYLA3R2B/bundle.json","state_url":"https://pith.science/pith/MLKWF7V7KLZES5QW4CVYLA3R2B/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MLKWF7V7KLZES5QW4CVYLA3R2B/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":"2026-06-11T03:58:19Z","links":{"resolver":"https://pith.science/pith/MLKWF7V7KLZES5QW4CVYLA3R2B","bundle":"https://pith.science/pith/MLKWF7V7KLZES5QW4CVYLA3R2B/bundle.json","state":"https://pith.science/pith/MLKWF7V7KLZES5QW4CVYLA3R2B/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MLKWF7V7KLZES5QW4CVYLA3R2B/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2007:MLKWF7V7KLZES5QW4CVYLA3R2B","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":"cab568fd32d202a62000dea92a4f8bdb29f486c1cbfc7b928faec3797f09f5cb","cross_cats_sorted":["math.PR","stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2007-08-01T14:54:16Z","title_canon_sha256":"e6eb14212a2666ad7f259e6dc969ff10ae0c8f10c4d53c302838f86cba7e69eb"},"schema_version":"1.0","source":{"id":"0708.0169","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"0708.0169","created_at":"2026-05-18T00:34:39Z"},{"alias_kind":"arxiv_version","alias_value":"0708.0169v4","created_at":"2026-05-18T00:34:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.0708.0169","created_at":"2026-05-18T00:34:39Z"},{"alias_kind":"pith_short_12","alias_value":"MLKWF7V7KLZE","created_at":"2026-05-18T12:25:55Z"},{"alias_kind":"pith_short_16","alias_value":"MLKWF7V7KLZES5QW","created_at":"2026-05-18T12:25:55Z"},{"alias_kind":"pith_short_8","alias_value":"MLKWF7V7","created_at":"2026-05-18T12:25:55Z"}],"graph_snapshots":[{"event_id":"sha256:2fd3659f0e3f4581d43077ebc0d9d5b908462a4a366292e9cca6fd306319ce66","target":"graph","created_at":"2026-05-18T00:34:39Z","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 propose and study a general method for construction of consistent statistical tests on the basis of possibly indirect, corrupted, or partially available observations. The class of tests devised in the paper contains Neyman's smooth tests, data-driven score tests, and some types of multi-sample tests as basic examples. Our tests are data-driven and are additionally incorporated with model selection rules. The method allows to use a wide class of model selection rules that are based on the penalization idea. In particular, many of the optimal penalties, derived in statistical literature, can ","authors_text":"Mikhail Langovoy","cross_cats":["math.PR","stat.ME","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2007-08-01T14:54:16Z","title":"Data-driven goodness-of-fit tests"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"0708.0169","kind":"arxiv","version":4},"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:c4dc170fe6c9a643b3e6c0caced9ce4f2769cae11e509924a54b092ede06831f","target":"record","created_at":"2026-05-18T00:34:39Z","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":"cab568fd32d202a62000dea92a4f8bdb29f486c1cbfc7b928faec3797f09f5cb","cross_cats_sorted":["math.PR","stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2007-08-01T14:54:16Z","title_canon_sha256":"e6eb14212a2666ad7f259e6dc969ff10ae0c8f10c4d53c302838f86cba7e69eb"},"schema_version":"1.0","source":{"id":"0708.0169","kind":"arxiv","version":4}},"canonical_sha256":"62d562febf52f2497616e0ab858371d06fe37685702130c492aadd119d1326f2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"62d562febf52f2497616e0ab858371d06fe37685702130c492aadd119d1326f2","first_computed_at":"2026-05-18T00:34:39.743294Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:34:39.743294Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1DNj/Zqt2gfdf5RbyPH8fPlJllg2HTejuHaUjIz4FAZ03L8eWitfVk3MUx0MV7bhaaVOwcB05xNAKNzqUhg6Cw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:34:39.744057Z","signed_message":"canonical_sha256_bytes"},"source_id":"0708.0169","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c4dc170fe6c9a643b3e6c0caced9ce4f2769cae11e509924a54b092ede06831f","sha256:2fd3659f0e3f4581d43077ebc0d9d5b908462a4a366292e9cca6fd306319ce66"],"state_sha256":"73c4e1f827b0acdbab14c41f979b07d1fd3340304866ea5fc2e6c361cc237bba"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+2MYQxbSP8rvze3ey9iH3LR7KivvZbrAaaHdDHfhJfjXKhonhRTTY5lL6dMctIeLcxp7KIvo/tR1olzhxSHgAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T03:58:19.266907Z","bundle_sha256":"3facc90abe28edba1b425d30ce0284360cac713675cfe5be8c7699da5f656dc6"}}