{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2010:ZF6Q6VFLVCGYJPGQA7X5LZPUSS","short_pith_number":"pith:ZF6Q6VFL","schema_version":"1.0","canonical_sha256":"c97d0f54aba88d84bcd007efd5e5f4948077c0d3b41f84855b6dbbef0a2dc098","source":{"kind":"arxiv","id":"1011.3333","version":1},"attestation_state":"computed","paper":{"title":"Optimal designs for random effect models with correlated errors with applications in population pharmacokinetics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Andrey Pepelyshev, Holger Dette, Tim Holland-Letz","submitted_at":"2010-11-15T10:29:24Z","abstract_excerpt":"We consider the problem of constructing optimal designs for population pharmacokinetics which use random effect models. It is common practice in the design of experiments in such studies to assume uncorrelated errors for each subject. In the present paper a new approach is introduced to determine efficient designs for nonlinear least squares estimation which addresses the problem of correlation between observations corresponding to the same subject. We use asymptotic arguments to derive optimal design densities, and the designs for finite sample sizes are constructed from the quantiles of the "},"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":"1011.3333","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2010-11-15T10:29:24Z","cross_cats_sorted":[],"title_canon_sha256":"47da19cdfc31ccb4ad3a691baf5b510417aceb0713758ddcdc29c899912723aa","abstract_canon_sha256":"2ea6bf31716ba21ee066bf71b797538ea7ade2d69b80f96c2fb19699e7dcc778"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:35:56.120265Z","signature_b64":"QSbrblKoAglTZc6gP882/CynOoMcwG5PVTl1oT+zg1Gg/GhFvI5nAnuRG6m5Rw1U/G4j6gBvnrNzxHJFrUafCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c97d0f54aba88d84bcd007efd5e5f4948077c0d3b41f84855b6dbbef0a2dc098","last_reissued_at":"2026-05-18T04:35:56.119860Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:35:56.119860Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Optimal designs for random effect models with correlated errors with applications in population pharmacokinetics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Andrey Pepelyshev, Holger Dette, Tim Holland-Letz","submitted_at":"2010-11-15T10:29:24Z","abstract_excerpt":"We consider the problem of constructing optimal designs for population pharmacokinetics which use random effect models. It is common practice in the design of experiments in such studies to assume uncorrelated errors for each subject. In the present paper a new approach is introduced to determine efficient designs for nonlinear least squares estimation which addresses the problem of correlation between observations corresponding to the same subject. We use asymptotic arguments to derive optimal design densities, and the designs for finite sample sizes are constructed from the quantiles of the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1011.3333","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":"1011.3333","created_at":"2026-05-18T04:35:56.119916+00:00"},{"alias_kind":"arxiv_version","alias_value":"1011.3333v1","created_at":"2026-05-18T04:35:56.119916+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1011.3333","created_at":"2026-05-18T04:35:56.119916+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZF6Q6VFLVCGY","created_at":"2026-05-18T12:26:17.028572+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZF6Q6VFLVCGYJPGQ","created_at":"2026-05-18T12:26:17.028572+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZF6Q6VFL","created_at":"2026-05-18T12:26:17.028572+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/ZF6Q6VFLVCGYJPGQA7X5LZPUSS","json":"https://pith.science/pith/ZF6Q6VFLVCGYJPGQA7X5LZPUSS.json","graph_json":"https://pith.science/api/pith-number/ZF6Q6VFLVCGYJPGQA7X5LZPUSS/graph.json","events_json":"https://pith.science/api/pith-number/ZF6Q6VFLVCGYJPGQA7X5LZPUSS/events.json","paper":"https://pith.science/paper/ZF6Q6VFL"},"agent_actions":{"view_html":"https://pith.science/pith/ZF6Q6VFLVCGYJPGQA7X5LZPUSS","download_json":"https://pith.science/pith/ZF6Q6VFLVCGYJPGQA7X5LZPUSS.json","view_paper":"https://pith.science/paper/ZF6Q6VFL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1011.3333&json=true","fetch_graph":"https://pith.science/api/pith-number/ZF6Q6VFLVCGYJPGQA7X5LZPUSS/graph.json","fetch_events":"https://pith.science/api/pith-number/ZF6Q6VFLVCGYJPGQA7X5LZPUSS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZF6Q6VFLVCGYJPGQA7X5LZPUSS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZF6Q6VFLVCGYJPGQA7X5LZPUSS/action/storage_attestation","attest_author":"https://pith.science/pith/ZF6Q6VFLVCGYJPGQA7X5LZPUSS/action/author_attestation","sign_citation":"https://pith.science/pith/ZF6Q6VFLVCGYJPGQA7X5LZPUSS/action/citation_signature","submit_replication":"https://pith.science/pith/ZF6Q6VFLVCGYJPGQA7X5LZPUSS/action/replication_record"}},"created_at":"2026-05-18T04:35:56.119916+00:00","updated_at":"2026-05-18T04:35:56.119916+00:00"}