{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:HYI6BCD7VHNHZC6LTJ7Y5RWXQV","short_pith_number":"pith:HYI6BCD7","canonical_record":{"source":{"id":"1703.08045","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-03-23T12:43:23Z","cross_cats_sorted":[],"title_canon_sha256":"fadf08916f3105ac95e0cd5987c2c9ba4ccdd5e4dd7efa4967263b5ce56fec60","abstract_canon_sha256":"cc998e8dad4de011b0a7485982bc89ed4f8c0fc95f4ba69dddc44721606072d6"},"schema_version":"1.0"},"canonical_sha256":"3e11e0887fa9da7c8bcb9a7f8ec6d7857adaf7f58cc4796032417707b9491968","source":{"kind":"arxiv","id":"1703.08045","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.08045","created_at":"2026-05-18T00:45:06Z"},{"alias_kind":"arxiv_version","alias_value":"1703.08045v2","created_at":"2026-05-18T00:45:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.08045","created_at":"2026-05-18T00:45:06Z"},{"alias_kind":"pith_short_12","alias_value":"HYI6BCD7VHNH","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"HYI6BCD7VHNHZC6L","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"HYI6BCD7","created_at":"2026-05-18T12:31:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:HYI6BCD7VHNHZC6LTJ7Y5RWXQV","target":"record","payload":{"canonical_record":{"source":{"id":"1703.08045","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-03-23T12:43:23Z","cross_cats_sorted":[],"title_canon_sha256":"fadf08916f3105ac95e0cd5987c2c9ba4ccdd5e4dd7efa4967263b5ce56fec60","abstract_canon_sha256":"cc998e8dad4de011b0a7485982bc89ed4f8c0fc95f4ba69dddc44721606072d6"},"schema_version":"1.0"},"canonical_sha256":"3e11e0887fa9da7c8bcb9a7f8ec6d7857adaf7f58cc4796032417707b9491968","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:45:06.061945Z","signature_b64":"+zJh1vtRw614aJVAC0h6iRqbDeO0Lb2FpHKwVlkEKWPpCqBnNQUHgTi5uP1h7Bj2ikbin38JrsqEfqisyLu+Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3e11e0887fa9da7c8bcb9a7f8ec6d7857adaf7f58cc4796032417707b9491968","last_reissued_at":"2026-05-18T00:45:06.061514Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:45:06.061514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1703.08045","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:45:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jUjy5aJcoeBQfPF2mVj1MIAryHzEGfN8KRsWMxFiOAsoaYdLPmh16JVNvqbGLIhMbrsK1Yv8LevvKtluGsZnBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-23T19:21:06.572760Z"},"content_sha256":"f982a695e136925f32a19f747e8e2a9651cb4b2761737873cf522f1020d81847","schema_version":"1.0","event_id":"sha256:f982a695e136925f32a19f747e8e2a9651cb4b2761737873cf522f1020d81847"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:HYI6BCD7VHNHZC6LTJ7Y5RWXQV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Profiled deviance for the multivariate linear mixed-effects model fitting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Eric Adjakossa (LPMA, Gr\\'egory Nuel (LPMA), UAC)","submitted_at":"2017-03-23T12:43:23Z","abstract_excerpt":"This paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the marginal residual terms are assumed uncorrelated and homoscedastic with possibly different standard deviations. The random effects covariance matrix is Cholesky factorized to directly estimate the variance components of these random effects. This strategy enables a consistent estimate of the random effects covariance matrix which, generally, has a poor estimate when it is grossly (or directly) estimated, using the estimating methods such as the EM algorithm. By "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.08045","kind":"arxiv","version":2},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:45:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CPyBM3tRdXB6tBl76JYT1bjMpPOhZwWIcgPfz+KNg16rlYtBtnuXfXZxFYwsS8ygQi/06C277llE+klOp3+iDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-23T19:21:06.573125Z"},"content_sha256":"a4ef7ebf0e6e73cc880635757675a28e8948401e75e0c18a7d6d41cbc25e52fe","schema_version":"1.0","event_id":"sha256:a4ef7ebf0e6e73cc880635757675a28e8948401e75e0c18a7d6d41cbc25e52fe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HYI6BCD7VHNHZC6LTJ7Y5RWXQV/bundle.json","state_url":"https://pith.science/pith/HYI6BCD7VHNHZC6LTJ7Y5RWXQV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HYI6BCD7VHNHZC6LTJ7Y5RWXQV/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-23T19:21:06Z","links":{"resolver":"https://pith.science/pith/HYI6BCD7VHNHZC6LTJ7Y5RWXQV","bundle":"https://pith.science/pith/HYI6BCD7VHNHZC6LTJ7Y5RWXQV/bundle.json","state":"https://pith.science/pith/HYI6BCD7VHNHZC6LTJ7Y5RWXQV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HYI6BCD7VHNHZC6LTJ7Y5RWXQV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:HYI6BCD7VHNHZC6LTJ7Y5RWXQV","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"cc998e8dad4de011b0a7485982bc89ed4f8c0fc95f4ba69dddc44721606072d6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-03-23T12:43:23Z","title_canon_sha256":"fadf08916f3105ac95e0cd5987c2c9ba4ccdd5e4dd7efa4967263b5ce56fec60"},"schema_version":"1.0","source":{"id":"1703.08045","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.08045","created_at":"2026-05-18T00:45:06Z"},{"alias_kind":"arxiv_version","alias_value":"1703.08045v2","created_at":"2026-05-18T00:45:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.08045","created_at":"2026-05-18T00:45:06Z"},{"alias_kind":"pith_short_12","alias_value":"HYI6BCD7VHNH","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"HYI6BCD7VHNHZC6L","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"HYI6BCD7","created_at":"2026-05-18T12:31:21Z"}],"graph_snapshots":[{"event_id":"sha256:a4ef7ebf0e6e73cc880635757675a28e8948401e75e0c18a7d6d41cbc25e52fe","target":"graph","created_at":"2026-05-18T00:45:06Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"This paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the marginal residual terms are assumed uncorrelated and homoscedastic with possibly different standard deviations. The random effects covariance matrix is Cholesky factorized to directly estimate the variance components of these random effects. This strategy enables a consistent estimate of the random effects covariance matrix which, generally, has a poor estimate when it is grossly (or directly) estimated, using the estimating methods such as the EM algorithm. By ","authors_text":"Eric Adjakossa (LPMA, Gr\\'egory Nuel (LPMA), UAC)","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-03-23T12:43:23Z","title":"Profiled deviance for the multivariate linear mixed-effects model fitting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.08045","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:f982a695e136925f32a19f747e8e2a9651cb4b2761737873cf522f1020d81847","target":"record","created_at":"2026-05-18T00:45:06Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"cc998e8dad4de011b0a7485982bc89ed4f8c0fc95f4ba69dddc44721606072d6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-03-23T12:43:23Z","title_canon_sha256":"fadf08916f3105ac95e0cd5987c2c9ba4ccdd5e4dd7efa4967263b5ce56fec60"},"schema_version":"1.0","source":{"id":"1703.08045","kind":"arxiv","version":2}},"canonical_sha256":"3e11e0887fa9da7c8bcb9a7f8ec6d7857adaf7f58cc4796032417707b9491968","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3e11e0887fa9da7c8bcb9a7f8ec6d7857adaf7f58cc4796032417707b9491968","first_computed_at":"2026-05-18T00:45:06.061514Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:45:06.061514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+zJh1vtRw614aJVAC0h6iRqbDeO0Lb2FpHKwVlkEKWPpCqBnNQUHgTi5uP1h7Bj2ikbin38JrsqEfqisyLu+Bw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:45:06.061945Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.08045","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f982a695e136925f32a19f747e8e2a9651cb4b2761737873cf522f1020d81847","sha256:a4ef7ebf0e6e73cc880635757675a28e8948401e75e0c18a7d6d41cbc25e52fe"],"state_sha256":"742cc1a9a0a1d171f4f2168230e5881e75c19a63169635977f0819a7dcf7506c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+lMbC936Q0gryhu1ycT6E8Ahi6OALRaF50382iEXNGABiFS/ssqHbpFjMScTofuN32rK+9K/sTEZhtHj4iUpCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-23T19:21:06.575058Z","bundle_sha256":"cb89d4fc1e0dfd25fddfa126a0d95c86e78e95264233a82b6d380a09f7243be1"}}