{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:2Y3UZS7A6J25IUGJOAXKDFZFNZ","short_pith_number":"pith:2Y3UZS7A","schema_version":"1.0","canonical_sha256":"d6374ccbe0f275d450c9702ea197256e60de9013eb9b0ee3b8bfa8c5e1924d7a","source":{"kind":"arxiv","id":"1110.6623","version":1},"attestation_state":"computed","paper":{"title":"A New Characterization of Elfving's Method for High Dimensional Computation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME","stat.TH"],"primary_cat":"math.ST","authors_text":"Jay Bartroff","submitted_at":"2011-10-30T16:59:26Z","abstract_excerpt":"We give a new characterization of Elfving's (1952) method for computing c-optimal designs in k dimensions which gives explicit formulae for the k unknown optimal weights and k unknown signs in Elfving's characterization. This eliminates the need to search over these parameters to compute c-optimal designs, and thus reduces the computational burden from solving a family of optimization problems to solving a single optimization problem for the optimal finite support set. We give two illustrative examples: a high dimensional polynomial regression model and a logistic regression model, the latter "},"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":"1110.6623","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2011-10-30T16:59:26Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"8f643aad9b53a7cc39fbfc49a01138ae6111be658a5304b56ca8327c10a32967","abstract_canon_sha256":"4ed6370a0091de1c29155fe98961a689f8d56ff78fa17854e43ae75622421680"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:09:55.046950Z","signature_b64":"bXNX4w6EqkAmaz9W+qyYJfQV3PBSC3XU7SHZySL65h/RFviLt1aILMvRHdMGVEGYwnr0aqBievvDPwdPX3qYAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6374ccbe0f275d450c9702ea197256e60de9013eb9b0ee3b8bfa8c5e1924d7a","last_reissued_at":"2026-05-18T04:09:55.045979Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:09:55.045979Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A New Characterization of Elfving's Method for High Dimensional Computation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME","stat.TH"],"primary_cat":"math.ST","authors_text":"Jay Bartroff","submitted_at":"2011-10-30T16:59:26Z","abstract_excerpt":"We give a new characterization of Elfving's (1952) method for computing c-optimal designs in k dimensions which gives explicit formulae for the k unknown optimal weights and k unknown signs in Elfving's characterization. This eliminates the need to search over these parameters to compute c-optimal designs, and thus reduces the computational burden from solving a family of optimization problems to solving a single optimization problem for the optimal finite support set. We give two illustrative examples: a high dimensional polynomial regression model and a logistic regression model, the latter "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1110.6623","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":"1110.6623","created_at":"2026-05-18T04:09:55.046145+00:00"},{"alias_kind":"arxiv_version","alias_value":"1110.6623v1","created_at":"2026-05-18T04:09:55.046145+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1110.6623","created_at":"2026-05-18T04:09:55.046145+00:00"},{"alias_kind":"pith_short_12","alias_value":"2Y3UZS7A6J25","created_at":"2026-05-18T12:26:18.847500+00:00"},{"alias_kind":"pith_short_16","alias_value":"2Y3UZS7A6J25IUGJ","created_at":"2026-05-18T12:26:18.847500+00:00"},{"alias_kind":"pith_short_8","alias_value":"2Y3UZS7A","created_at":"2026-05-18T12:26:18.847500+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/2Y3UZS7A6J25IUGJOAXKDFZFNZ","json":"https://pith.science/pith/2Y3UZS7A6J25IUGJOAXKDFZFNZ.json","graph_json":"https://pith.science/api/pith-number/2Y3UZS7A6J25IUGJOAXKDFZFNZ/graph.json","events_json":"https://pith.science/api/pith-number/2Y3UZS7A6J25IUGJOAXKDFZFNZ/events.json","paper":"https://pith.science/paper/2Y3UZS7A"},"agent_actions":{"view_html":"https://pith.science/pith/2Y3UZS7A6J25IUGJOAXKDFZFNZ","download_json":"https://pith.science/pith/2Y3UZS7A6J25IUGJOAXKDFZFNZ.json","view_paper":"https://pith.science/paper/2Y3UZS7A","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1110.6623&json=true","fetch_graph":"https://pith.science/api/pith-number/2Y3UZS7A6J25IUGJOAXKDFZFNZ/graph.json","fetch_events":"https://pith.science/api/pith-number/2Y3UZS7A6J25IUGJOAXKDFZFNZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2Y3UZS7A6J25IUGJOAXKDFZFNZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2Y3UZS7A6J25IUGJOAXKDFZFNZ/action/storage_attestation","attest_author":"https://pith.science/pith/2Y3UZS7A6J25IUGJOAXKDFZFNZ/action/author_attestation","sign_citation":"https://pith.science/pith/2Y3UZS7A6J25IUGJOAXKDFZFNZ/action/citation_signature","submit_replication":"https://pith.science/pith/2Y3UZS7A6J25IUGJOAXKDFZFNZ/action/replication_record"}},"created_at":"2026-05-18T04:09:55.046145+00:00","updated_at":"2026-05-18T04:09:55.046145+00:00"}