{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:WVVNB4BFE3WCFTUXQTARO2TY37","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":"99ac30d3d5ee96b82c37fc0d89ffb7b1437b8faee159834d4d21ae38bfceaead","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-06-01T12:48:43Z","title_canon_sha256":"b36c40676b88fe8fe1807a60785ad4369c6a60343891c90adc77e2088cedc5ad"},"schema_version":"1.0","source":{"id":"1606.00263","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1606.00263","created_at":"2026-05-18T01:13:05Z"},{"alias_kind":"arxiv_version","alias_value":"1606.00263v1","created_at":"2026-05-18T01:13:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.00263","created_at":"2026-05-18T01:13:05Z"},{"alias_kind":"pith_short_12","alias_value":"WVVNB4BFE3WC","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_16","alias_value":"WVVNB4BFE3WCFTUX","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_8","alias_value":"WVVNB4BF","created_at":"2026-05-18T12:30:51Z"}],"graph_snapshots":[{"event_id":"sha256:e143250500463b499cbdd68ed90c392c661a58f3e6a9a6f730be537b64484584","target":"graph","created_at":"2026-05-18T01:13:05Z","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 an earlier paper Rakonczai et al. (2014), we have emphasized the effective sample size for autocorrelated data. The simulations were based on the block bootstrap methodology. However, the discreteness of the usual block size did not allow for exact calculations. In this paper we propose a generalisation of the block bootstrap methodology, relate it to the existing optimisation procedures and apply it to a temperature data set. Our other focus is on statistical tests, where quite often the actual sample size plays an important role, even in case of relatively large samples. This is especiall","authors_text":"Andr\\'as Zempl\\'eni, L\\'aszl\\'o Varga","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-06-01T12:48:43Z","title":"Generalised block bootstrap and its use in meteorology"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.00263","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":"sha256:32c1647377dd522cecff3d5913081fb6295acc3ae3e3d8662f6a146848ee31c4","target":"record","created_at":"2026-05-18T01:13:05Z","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":"99ac30d3d5ee96b82c37fc0d89ffb7b1437b8faee159834d4d21ae38bfceaead","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-06-01T12:48:43Z","title_canon_sha256":"b36c40676b88fe8fe1807a60785ad4369c6a60343891c90adc77e2088cedc5ad"},"schema_version":"1.0","source":{"id":"1606.00263","kind":"arxiv","version":1}},"canonical_sha256":"b56ad0f02526ec22ce9784c1176a78dff11db9ad797be020d396b8271b694985","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b56ad0f02526ec22ce9784c1176a78dff11db9ad797be020d396b8271b694985","first_computed_at":"2026-05-18T01:13:05.646973Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:13:05.646973Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QrPe/wHUsxcYZ52+461mHPGLV8EWmifYY0xkP6Jk0G4jvwOBOQFrPrgiqwn+WoZtPK90bQRhHomJDUruZp/7Aw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:13:05.647375Z","signed_message":"canonical_sha256_bytes"},"source_id":"1606.00263","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:32c1647377dd522cecff3d5913081fb6295acc3ae3e3d8662f6a146848ee31c4","sha256:e143250500463b499cbdd68ed90c392c661a58f3e6a9a6f730be537b64484584"],"state_sha256":"f7fe09ac66d6a12a1f928d7c164b32d47b625fb60eebd2772040a2a903f028c2"}