{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:IILGHVUN2I7JB35UBXLOXZ4ZLF","short_pith_number":"pith:IILGHVUN","schema_version":"1.0","canonical_sha256":"421663d68dd23e90efb40dd6ebe799595b1d610ad5372192dc199154f16826ce","source":{"kind":"arxiv","id":"1312.6815","version":5},"attestation_state":"computed","paper":{"title":"A goodness-of-fit test based on the empirical characteristic function and a comparison of tests for normality","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"J. Martin van Zyl","submitted_at":"2013-12-24T13:33:34Z","abstract_excerpt":"The normal distribution has the unique property that the cumulant generating function has only two terms, namely those involving the mean and the variance. This property is used to construct a simple by using the log of the modulus of the empirical characteristic function to what would be expected under normality. The test statistic is easy to calculate. Using a simulation study the proposed test is shown to have excellent power, especially in large samples."},"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":"1312.6815","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2013-12-24T13:33:34Z","cross_cats_sorted":[],"title_canon_sha256":"57dab959b2a905f2346c32e6b496c4c4991f58af2bfe32db337d7dbbd4566a4b","abstract_canon_sha256":"a764c95acfbcbe4bacb0ae217fbb93398ddbb9d703433f2b6b1d2d6c5b4143e0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:16:03.047887Z","signature_b64":"pBt+ZkbEs5tYATeQ+BSrDVCB44jjzSQQJtH09ofohiLbdLj2YUBvcc02QQDRtFRFpHZfgLO3gcT6SvNSiiQjDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"421663d68dd23e90efb40dd6ebe799595b1d610ad5372192dc199154f16826ce","last_reissued_at":"2026-05-18T01:16:03.047153Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:16:03.047153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A goodness-of-fit test based on the empirical characteristic function and a comparison of tests for normality","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"J. Martin van Zyl","submitted_at":"2013-12-24T13:33:34Z","abstract_excerpt":"The normal distribution has the unique property that the cumulant generating function has only two terms, namely those involving the mean and the variance. This property is used to construct a simple by using the log of the modulus of the empirical characteristic function to what would be expected under normality. The test statistic is easy to calculate. Using a simulation study the proposed test is shown to have excellent power, especially in large samples."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1312.6815","kind":"arxiv","version":5},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1312.6815","created_at":"2026-05-18T01:16:03.047271+00:00"},{"alias_kind":"arxiv_version","alias_value":"1312.6815v5","created_at":"2026-05-18T01:16:03.047271+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1312.6815","created_at":"2026-05-18T01:16:03.047271+00:00"},{"alias_kind":"pith_short_12","alias_value":"IILGHVUN2I7J","created_at":"2026-05-18T12:27:46.883200+00:00"},{"alias_kind":"pith_short_16","alias_value":"IILGHVUN2I7JB35U","created_at":"2026-05-18T12:27:46.883200+00:00"},{"alias_kind":"pith_short_8","alias_value":"IILGHVUN","created_at":"2026-05-18T12:27:46.883200+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/IILGHVUN2I7JB35UBXLOXZ4ZLF","json":"https://pith.science/pith/IILGHVUN2I7JB35UBXLOXZ4ZLF.json","graph_json":"https://pith.science/api/pith-number/IILGHVUN2I7JB35UBXLOXZ4ZLF/graph.json","events_json":"https://pith.science/api/pith-number/IILGHVUN2I7JB35UBXLOXZ4ZLF/events.json","paper":"https://pith.science/paper/IILGHVUN"},"agent_actions":{"view_html":"https://pith.science/pith/IILGHVUN2I7JB35UBXLOXZ4ZLF","download_json":"https://pith.science/pith/IILGHVUN2I7JB35UBXLOXZ4ZLF.json","view_paper":"https://pith.science/paper/IILGHVUN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1312.6815&json=true","fetch_graph":"https://pith.science/api/pith-number/IILGHVUN2I7JB35UBXLOXZ4ZLF/graph.json","fetch_events":"https://pith.science/api/pith-number/IILGHVUN2I7JB35UBXLOXZ4ZLF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IILGHVUN2I7JB35UBXLOXZ4ZLF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IILGHVUN2I7JB35UBXLOXZ4ZLF/action/storage_attestation","attest_author":"https://pith.science/pith/IILGHVUN2I7JB35UBXLOXZ4ZLF/action/author_attestation","sign_citation":"https://pith.science/pith/IILGHVUN2I7JB35UBXLOXZ4ZLF/action/citation_signature","submit_replication":"https://pith.science/pith/IILGHVUN2I7JB35UBXLOXZ4ZLF/action/replication_record"}},"created_at":"2026-05-18T01:16:03.047271+00:00","updated_at":"2026-05-18T01:16:03.047271+00:00"}