{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:546FQC6VSBE7HWZIY5IS4ORE6A","short_pith_number":"pith:546FQC6V","schema_version":"1.0","canonical_sha256":"ef3c580bd59049f3db28c7512e3a24f0129d13bbf809fb135727e7cef9d8e7a8","source":{"kind":"arxiv","id":"2305.15019","version":1},"attestation_state":"computed","paper":{"title":"A comparison of estimators of mean and its functions in finite populations","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["stat.ME","stat.TH"],"primary_cat":"math.ST","authors_text":"Anurag Dey, Probal Chaudhuri","submitted_at":"2023-05-24T11:00:07Z","abstract_excerpt":"Several well known estimators of finite population mean and its functions are investigated under some standard sampling designs. Such functions of mean include the variance, the correlation coefficient and the regression coefficient in the population as special cases. We compare the performance of these estimators under different sampling designs based on their asymptotic distributions. Equivalence classes of estimators under different sampling designs are constructed so that estimators in the same class have equivalent performance in terms of asymptotic mean squared errors (MSEs). Estimators "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2305.15019","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"math.ST","submitted_at":"2023-05-24T11:00:07Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"7b0bd3970ba3f8580dd36fecead5335171857a9f3afa6f656bed6da4a68f3de6","abstract_canon_sha256":"c99f0d5297513a8cb27f302356b179512bb40bb58d57e5629fecea736ead66d0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:13:30.175344Z","signature_b64":"SBtcbCRU7XnCY5w0cMVKMlHEYArWj9jiipOTPwsFoc1i/Vm4Gc/fFp1st0DQnkm8fNqP1RKWZQE2gBqUa9l+CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ef3c580bd59049f3db28c7512e3a24f0129d13bbf809fb135727e7cef9d8e7a8","last_reissued_at":"2026-07-05T06:13:30.174909Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:13:30.174909Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A comparison of estimators of mean and its functions in finite populations","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["stat.ME","stat.TH"],"primary_cat":"math.ST","authors_text":"Anurag Dey, Probal Chaudhuri","submitted_at":"2023-05-24T11:00:07Z","abstract_excerpt":"Several well known estimators of finite population mean and its functions are investigated under some standard sampling designs. Such functions of mean include the variance, the correlation coefficient and the regression coefficient in the population as special cases. We compare the performance of these estimators under different sampling designs based on their asymptotic distributions. Equivalence classes of estimators under different sampling designs are constructed so that estimators in the same class have equivalent performance in terms of asymptotic mean squared errors (MSEs). Estimators "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.15019","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2305.15019/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2305.15019","created_at":"2026-07-05T06:13:30.174962+00:00"},{"alias_kind":"arxiv_version","alias_value":"2305.15019v1","created_at":"2026-07-05T06:13:30.174962+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.15019","created_at":"2026-07-05T06:13:30.174962+00:00"},{"alias_kind":"pith_short_12","alias_value":"546FQC6VSBE7","created_at":"2026-07-05T06:13:30.174962+00:00"},{"alias_kind":"pith_short_16","alias_value":"546FQC6VSBE7HWZI","created_at":"2026-07-05T06:13:30.174962+00:00"},{"alias_kind":"pith_short_8","alias_value":"546FQC6V","created_at":"2026-07-05T06:13:30.174962+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2505.23714","citing_title":"SenWiCh: Sense-Annotation of Low-Resource Languages for WiC using Hybrid Methods","ref_index":39,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/546FQC6VSBE7HWZIY5IS4ORE6A","json":"https://pith.science/pith/546FQC6VSBE7HWZIY5IS4ORE6A.json","graph_json":"https://pith.science/api/pith-number/546FQC6VSBE7HWZIY5IS4ORE6A/graph.json","events_json":"https://pith.science/api/pith-number/546FQC6VSBE7HWZIY5IS4ORE6A/events.json","paper":"https://pith.science/paper/546FQC6V"},"agent_actions":{"view_html":"https://pith.science/pith/546FQC6VSBE7HWZIY5IS4ORE6A","download_json":"https://pith.science/pith/546FQC6VSBE7HWZIY5IS4ORE6A.json","view_paper":"https://pith.science/paper/546FQC6V","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2305.15019&json=true","fetch_graph":"https://pith.science/api/pith-number/546FQC6VSBE7HWZIY5IS4ORE6A/graph.json","fetch_events":"https://pith.science/api/pith-number/546FQC6VSBE7HWZIY5IS4ORE6A/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/546FQC6VSBE7HWZIY5IS4ORE6A/action/timestamp_anchor","attest_storage":"https://pith.science/pith/546FQC6VSBE7HWZIY5IS4ORE6A/action/storage_attestation","attest_author":"https://pith.science/pith/546FQC6VSBE7HWZIY5IS4ORE6A/action/author_attestation","sign_citation":"https://pith.science/pith/546FQC6VSBE7HWZIY5IS4ORE6A/action/citation_signature","submit_replication":"https://pith.science/pith/546FQC6VSBE7HWZIY5IS4ORE6A/action/replication_record"}},"created_at":"2026-07-05T06:13:30.174962+00:00","updated_at":"2026-07-05T06:13:30.174962+00:00"}