{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:LOATL2RE6525RDK76QKHTP5JGE","short_pith_number":"pith:LOATL2RE","schema_version":"1.0","canonical_sha256":"5b8135ea24f775d88d5ff41479bfa9313a21180be20e14d344bbae923de19a33","source":{"kind":"arxiv","id":"1609.00736","version":1},"attestation_state":"computed","paper":{"title":"A robust covariance testing approach for high-throughput data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Yi-Hui Zhou","submitted_at":"2016-09-02T20:05:30Z","abstract_excerpt":"The problem of testing changes in covariance has received increasing attention in recent years, especially in the context of high-dimensional testing. A number of approaches have been proposed, all limited to the two-sample problem and involving varying statistics and assumptions on the number of features $p$ vs. the sample size $n$. There are no general approaches to test association of covariances with a continuous outcome. We propose a uniform framework for testing association of covariances with an experimental variable, whether discrete or continuous. The approach is not limited by the da"},"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":"1609.00736","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-09-02T20:05:30Z","cross_cats_sorted":[],"title_canon_sha256":"de09f9e8df20d382c61e2d0d274b92ea028782932275c9f7e4cae99bdca794d3","abstract_canon_sha256":"0474512e3267a71d0f3f302f79e70cb17d2f627e8939b6de711ea4591df7633b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:06:20.077114Z","signature_b64":"qyYWvwGLXLSCgZEM8v1xARVk8rhN9NShma84NHTIMAf/5s3Yzm0ISGs0KRDaEDvCaUbEmxXM1/BQg1rWtBvRCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5b8135ea24f775d88d5ff41479bfa9313a21180be20e14d344bbae923de19a33","last_reissued_at":"2026-05-18T01:06:20.076484Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:06:20.076484Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A robust covariance testing approach for high-throughput data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Yi-Hui Zhou","submitted_at":"2016-09-02T20:05:30Z","abstract_excerpt":"The problem of testing changes in covariance has received increasing attention in recent years, especially in the context of high-dimensional testing. A number of approaches have been proposed, all limited to the two-sample problem and involving varying statistics and assumptions on the number of features $p$ vs. the sample size $n$. There are no general approaches to test association of covariances with a continuous outcome. We propose a uniform framework for testing association of covariances with an experimental variable, whether discrete or continuous. The approach is not limited by the da"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.00736","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1609.00736","created_at":"2026-05-18T01:06:20.076603+00:00"},{"alias_kind":"arxiv_version","alias_value":"1609.00736v1","created_at":"2026-05-18T01:06:20.076603+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.00736","created_at":"2026-05-18T01:06:20.076603+00:00"},{"alias_kind":"pith_short_12","alias_value":"LOATL2RE6525","created_at":"2026-05-18T12:30:29.479603+00:00"},{"alias_kind":"pith_short_16","alias_value":"LOATL2RE6525RDK7","created_at":"2026-05-18T12:30:29.479603+00:00"},{"alias_kind":"pith_short_8","alias_value":"LOATL2RE","created_at":"2026-05-18T12:30:29.479603+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/LOATL2RE6525RDK76QKHTP5JGE","json":"https://pith.science/pith/LOATL2RE6525RDK76QKHTP5JGE.json","graph_json":"https://pith.science/api/pith-number/LOATL2RE6525RDK76QKHTP5JGE/graph.json","events_json":"https://pith.science/api/pith-number/LOATL2RE6525RDK76QKHTP5JGE/events.json","paper":"https://pith.science/paper/LOATL2RE"},"agent_actions":{"view_html":"https://pith.science/pith/LOATL2RE6525RDK76QKHTP5JGE","download_json":"https://pith.science/pith/LOATL2RE6525RDK76QKHTP5JGE.json","view_paper":"https://pith.science/paper/LOATL2RE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1609.00736&json=true","fetch_graph":"https://pith.science/api/pith-number/LOATL2RE6525RDK76QKHTP5JGE/graph.json","fetch_events":"https://pith.science/api/pith-number/LOATL2RE6525RDK76QKHTP5JGE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LOATL2RE6525RDK76QKHTP5JGE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LOATL2RE6525RDK76QKHTP5JGE/action/storage_attestation","attest_author":"https://pith.science/pith/LOATL2RE6525RDK76QKHTP5JGE/action/author_attestation","sign_citation":"https://pith.science/pith/LOATL2RE6525RDK76QKHTP5JGE/action/citation_signature","submit_replication":"https://pith.science/pith/LOATL2RE6525RDK76QKHTP5JGE/action/replication_record"}},"created_at":"2026-05-18T01:06:20.076603+00:00","updated_at":"2026-05-18T01:06:20.076603+00:00"}