{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:S7BRJBNZYHKKDROEXKJGSD5HCM","short_pith_number":"pith:S7BRJBNZ","canonical_record":{"source":{"id":"1510.00551","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-10-02T10:26:57Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"15248e53662a5be5665d8d8d8b367313c6c33d7d1e6c120adffcba118a873565","abstract_canon_sha256":"637c193b3d3972f7e054fd8d4aa6df1b7be925d020faabc3e2b9ee93bff8210b"},"schema_version":"1.0"},"canonical_sha256":"97c31485b9c1d4a1c5c4ba92690fa7132b8194ea6a0d2ca848b7e8bcfeee3f65","source":{"kind":"arxiv","id":"1510.00551","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1510.00551","created_at":"2026-05-17T23:40:05Z"},{"alias_kind":"arxiv_version","alias_value":"1510.00551v5","created_at":"2026-05-17T23:40:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1510.00551","created_at":"2026-05-17T23:40:05Z"},{"alias_kind":"pith_short_12","alias_value":"S7BRJBNZYHKK","created_at":"2026-05-18T12:29:39Z"},{"alias_kind":"pith_short_16","alias_value":"S7BRJBNZYHKKDROE","created_at":"2026-05-18T12:29:39Z"},{"alias_kind":"pith_short_8","alias_value":"S7BRJBNZ","created_at":"2026-05-18T12:29:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:S7BRJBNZYHKKDROEXKJGSD5HCM","target":"record","payload":{"canonical_record":{"source":{"id":"1510.00551","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-10-02T10:26:57Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"15248e53662a5be5665d8d8d8b367313c6c33d7d1e6c120adffcba118a873565","abstract_canon_sha256":"637c193b3d3972f7e054fd8d4aa6df1b7be925d020faabc3e2b9ee93bff8210b"},"schema_version":"1.0"},"canonical_sha256":"97c31485b9c1d4a1c5c4ba92690fa7132b8194ea6a0d2ca848b7e8bcfeee3f65","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:05.039228Z","signature_b64":"GMi6MjnmUIqb1snywxxTHlu4safjdKo8L2c9IPsf+thvfqFf0/9unSLOCSqiq0tzyJWpESEJLPrlG52zvqkdDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"97c31485b9c1d4a1c5c4ba92690fa7132b8194ea6a0d2ca848b7e8bcfeee3f65","last_reissued_at":"2026-05-17T23:40:05.038523Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:05.038523Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1510.00551","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:40:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4U1htNKrHJcP2XZkO94pTZ3fyMpv/JJiA2hMYlWvE/fTj3NVtp4Utfatzg6nLVswfIfdGWizrMRm3WsgXpx0Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T19:56:12.810542Z"},"content_sha256":"ff598555131d124358637fa6130d50149b033d6a2ddd762b0f6359341fda222e","schema_version":"1.0","event_id":"sha256:ff598555131d124358637fa6130d50149b033d6a2ddd762b0f6359341fda222e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:S7BRJBNZYHKKDROEXKJGSD5HCM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Investigation of Parameter Uncertainty in Clustering Using a Gaussian Mixture Model Via Jackknife, Bootstrap and Weighted Likelihood Bootstrap","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"stat.CO","authors_text":"Adrian O'Hagan, Isobel Claire Gormley, Luca Scrucca, Thomas Brendan Murphy","submitted_at":"2015-10-02T10:26:57Z","abstract_excerpt":"Mixture models are a popular tool in model-based clustering. Such a model is often fitted by a procedure that maximizes the likelihood, such as the EM algorithm. At convergence, the maximum likelihood parameter estimates are typically reported, but in most cases little emphasis is placed on the variability associated with these estimates. In part this may be due to the fact that standard errors are not directly calculated in the model-fitting algorithm, either because they are not required to fit the model, or because they are difficult to compute. The examination of standard errors in model-b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.00551","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:40:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hbhYYO+tO0Y845reimA3xtnFZ/yZONA++11Gik0OF+wbfjxsRpMxjWKvZFVR38kMLdU3iUtLqajIGiEtFqMlDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T19:56:12.810892Z"},"content_sha256":"a8a30053782b6609bf475065e5d778a2c2de9ae8d67e467613dea88ffddca2e0","schema_version":"1.0","event_id":"sha256:a8a30053782b6609bf475065e5d778a2c2de9ae8d67e467613dea88ffddca2e0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S7BRJBNZYHKKDROEXKJGSD5HCM/bundle.json","state_url":"https://pith.science/pith/S7BRJBNZYHKKDROEXKJGSD5HCM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S7BRJBNZYHKKDROEXKJGSD5HCM/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":"2026-06-02T19:56:12Z","links":{"resolver":"https://pith.science/pith/S7BRJBNZYHKKDROEXKJGSD5HCM","bundle":"https://pith.science/pith/S7BRJBNZYHKKDROEXKJGSD5HCM/bundle.json","state":"https://pith.science/pith/S7BRJBNZYHKKDROEXKJGSD5HCM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S7BRJBNZYHKKDROEXKJGSD5HCM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:S7BRJBNZYHKKDROEXKJGSD5HCM","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":"637c193b3d3972f7e054fd8d4aa6df1b7be925d020faabc3e2b9ee93bff8210b","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-10-02T10:26:57Z","title_canon_sha256":"15248e53662a5be5665d8d8d8b367313c6c33d7d1e6c120adffcba118a873565"},"schema_version":"1.0","source":{"id":"1510.00551","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1510.00551","created_at":"2026-05-17T23:40:05Z"},{"alias_kind":"arxiv_version","alias_value":"1510.00551v5","created_at":"2026-05-17T23:40:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1510.00551","created_at":"2026-05-17T23:40:05Z"},{"alias_kind":"pith_short_12","alias_value":"S7BRJBNZYHKK","created_at":"2026-05-18T12:29:39Z"},{"alias_kind":"pith_short_16","alias_value":"S7BRJBNZYHKKDROE","created_at":"2026-05-18T12:29:39Z"},{"alias_kind":"pith_short_8","alias_value":"S7BRJBNZ","created_at":"2026-05-18T12:29:39Z"}],"graph_snapshots":[{"event_id":"sha256:a8a30053782b6609bf475065e5d778a2c2de9ae8d67e467613dea88ffddca2e0","target":"graph","created_at":"2026-05-17T23:40:05Z","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":"Mixture models are a popular tool in model-based clustering. Such a model is often fitted by a procedure that maximizes the likelihood, such as the EM algorithm. At convergence, the maximum likelihood parameter estimates are typically reported, but in most cases little emphasis is placed on the variability associated with these estimates. In part this may be due to the fact that standard errors are not directly calculated in the model-fitting algorithm, either because they are not required to fit the model, or because they are difficult to compute. The examination of standard errors in model-b","authors_text":"Adrian O'Hagan, Isobel Claire Gormley, Luca Scrucca, Thomas Brendan Murphy","cross_cats":["stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-10-02T10:26:57Z","title":"Investigation of Parameter Uncertainty in Clustering Using a Gaussian Mixture Model Via Jackknife, Bootstrap and Weighted Likelihood Bootstrap"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.00551","kind":"arxiv","version":5},"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:ff598555131d124358637fa6130d50149b033d6a2ddd762b0f6359341fda222e","target":"record","created_at":"2026-05-17T23:40:05Z","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":"637c193b3d3972f7e054fd8d4aa6df1b7be925d020faabc3e2b9ee93bff8210b","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-10-02T10:26:57Z","title_canon_sha256":"15248e53662a5be5665d8d8d8b367313c6c33d7d1e6c120adffcba118a873565"},"schema_version":"1.0","source":{"id":"1510.00551","kind":"arxiv","version":5}},"canonical_sha256":"97c31485b9c1d4a1c5c4ba92690fa7132b8194ea6a0d2ca848b7e8bcfeee3f65","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"97c31485b9c1d4a1c5c4ba92690fa7132b8194ea6a0d2ca848b7e8bcfeee3f65","first_computed_at":"2026-05-17T23:40:05.038523Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:40:05.038523Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GMi6MjnmUIqb1snywxxTHlu4safjdKo8L2c9IPsf+thvfqFf0/9unSLOCSqiq0tzyJWpESEJLPrlG52zvqkdDQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:40:05.039228Z","signed_message":"canonical_sha256_bytes"},"source_id":"1510.00551","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ff598555131d124358637fa6130d50149b033d6a2ddd762b0f6359341fda222e","sha256:a8a30053782b6609bf475065e5d778a2c2de9ae8d67e467613dea88ffddca2e0"],"state_sha256":"2fd79e957a9e1bcb1da54c6dd5602fa46542a64a4160c8988b98b34290554f82"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HSt1tbtpbRcQZff13HIlf3v4JtspuVL4Cutpjamg4dZGKY1uegwm97jVnAIQuSVITz+Kdb+cl3b/mlJCjJmWDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T19:56:12.812855Z","bundle_sha256":"aed75d37b9c1e5c5a1097f38ba3ef886dc56fc01bb0c9415795da68aa695003e"}}