{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:7NQ4PVHCXCQCZJS4XKXQ4VGJJI","short_pith_number":"pith:7NQ4PVHC","canonical_record":{"source":{"id":"2411.18957","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-11-28T07:04:57Z","cross_cats_sorted":["stat.CO"],"title_canon_sha256":"fa097067d655901294f954b7e6cd951a0f24b28d22908268312bea9e4ba6b076","abstract_canon_sha256":"543861f848fa2a3381237739ea3b2f9f2c70c9fdff4f73c79555de344a290032"},"schema_version":"1.0"},"canonical_sha256":"fb61c7d4e2b8a02ca65cbaaf0e54c94a1449aaf76274006f6d33a3c01662a5b3","source":{"kind":"arxiv","id":"2411.18957","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.18957","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"arxiv_version","alias_value":"2411.18957v2","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.18957","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"pith_short_12","alias_value":"7NQ4PVHCXCQC","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"pith_short_16","alias_value":"7NQ4PVHCXCQCZJS4","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"pith_short_8","alias_value":"7NQ4PVHC","created_at":"2026-05-26T01:03:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:7NQ4PVHCXCQCZJS4XKXQ4VGJJI","target":"record","payload":{"canonical_record":{"source":{"id":"2411.18957","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-11-28T07:04:57Z","cross_cats_sorted":["stat.CO"],"title_canon_sha256":"fa097067d655901294f954b7e6cd951a0f24b28d22908268312bea9e4ba6b076","abstract_canon_sha256":"543861f848fa2a3381237739ea3b2f9f2c70c9fdff4f73c79555de344a290032"},"schema_version":"1.0"},"canonical_sha256":"fb61c7d4e2b8a02ca65cbaaf0e54c94a1449aaf76274006f6d33a3c01662a5b3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T01:03:09.706329Z","signature_b64":"Getlu7HzOJ/6lbVcJmj48xPWLiCMmCWoBamlXJS9qsFtaTi4uwuTnyEDWIsOjiazvXkruNhSEsTbS2rpBaS9AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fb61c7d4e2b8a02ca65cbaaf0e54c94a1449aaf76274006f6d33a3c01662a5b3","last_reissued_at":"2026-05-26T01:03:09.705488Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T01:03:09.705488Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.18957","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":"2026-05-26T01:03:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oZ5msdwMJKip4kxw8CdXXcARLkWbaGFW/mB+ppDNOHl2TGDZFlQUO931yYHlmQ+yIeKK92A8cjn73yRj3uuxAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T17:19:58.494934Z"},"content_sha256":"6dc00a31e925758170b77c669e03b281bc3a66201d309abed386f0ad19161fec","schema_version":"1.0","event_id":"sha256:6dc00a31e925758170b77c669e03b281bc3a66201d309abed386f0ad19161fec"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:7NQ4PVHCXCQCZJS4XKXQ4VGJJI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian Cluster Weighted Gaussian Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.CO"],"primary_cat":"stat.ME","authors_text":"Konstantinos Perrakis, Panagiotis Papastamoulis","submitted_at":"2024-11-28T07:04:57Z","abstract_excerpt":"We introduce a novel class of Bayesian mixtures for normal linear regression models which incorporates a further Gaussian random component for the distribution of the predictor variables. The proposed cluster-weighted model aims to encompass potential heterogeneity in the distribution of the response variable as well as in the multivariate distribution of the covariates for detecting signals relevant to the underlying latent structure. Of particular interest are potential signals originating from: (i) the linear predictor structures of the regression models and (ii) the covariance structures o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.18957","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2411.18957/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-05-26T01:03:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WeO2xemI11s+j6TUupiByxYajyGRumjOZR9l3+vToYBphYDu/vnDq37WytfA7lhNhSZBmI374K5blRWtKrIzBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T17:19:58.495305Z"},"content_sha256":"e94d0dde5300c5124f5fbd12f7cf2dcf7a815f846b887828fd8cb200f80d6ad0","schema_version":"1.0","event_id":"sha256:e94d0dde5300c5124f5fbd12f7cf2dcf7a815f846b887828fd8cb200f80d6ad0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7NQ4PVHCXCQCZJS4XKXQ4VGJJI/bundle.json","state_url":"https://pith.science/pith/7NQ4PVHCXCQCZJS4XKXQ4VGJJI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7NQ4PVHCXCQCZJS4XKXQ4VGJJI/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":"2026-07-01T17:19:58Z","links":{"resolver":"https://pith.science/pith/7NQ4PVHCXCQCZJS4XKXQ4VGJJI","bundle":"https://pith.science/pith/7NQ4PVHCXCQCZJS4XKXQ4VGJJI/bundle.json","state":"https://pith.science/pith/7NQ4PVHCXCQCZJS4XKXQ4VGJJI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7NQ4PVHCXCQCZJS4XKXQ4VGJJI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:7NQ4PVHCXCQCZJS4XKXQ4VGJJI","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":"543861f848fa2a3381237739ea3b2f9f2c70c9fdff4f73c79555de344a290032","cross_cats_sorted":["stat.CO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-11-28T07:04:57Z","title_canon_sha256":"fa097067d655901294f954b7e6cd951a0f24b28d22908268312bea9e4ba6b076"},"schema_version":"1.0","source":{"id":"2411.18957","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.18957","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"arxiv_version","alias_value":"2411.18957v2","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.18957","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"pith_short_12","alias_value":"7NQ4PVHCXCQC","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"pith_short_16","alias_value":"7NQ4PVHCXCQCZJS4","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"pith_short_8","alias_value":"7NQ4PVHC","created_at":"2026-05-26T01:03:09Z"}],"graph_snapshots":[{"event_id":"sha256:e94d0dde5300c5124f5fbd12f7cf2dcf7a815f846b887828fd8cb200f80d6ad0","target":"graph","created_at":"2026-05-26T01:03:09Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2411.18957/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce a novel class of Bayesian mixtures for normal linear regression models which incorporates a further Gaussian random component for the distribution of the predictor variables. The proposed cluster-weighted model aims to encompass potential heterogeneity in the distribution of the response variable as well as in the multivariate distribution of the covariates for detecting signals relevant to the underlying latent structure. Of particular interest are potential signals originating from: (i) the linear predictor structures of the regression models and (ii) the covariance structures o","authors_text":"Konstantinos Perrakis, Panagiotis Papastamoulis","cross_cats":["stat.CO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-11-28T07:04:57Z","title":"Bayesian Cluster Weighted Gaussian Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.18957","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":"sha256:6dc00a31e925758170b77c669e03b281bc3a66201d309abed386f0ad19161fec","target":"record","created_at":"2026-05-26T01:03:09Z","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":"543861f848fa2a3381237739ea3b2f9f2c70c9fdff4f73c79555de344a290032","cross_cats_sorted":["stat.CO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2024-11-28T07:04:57Z","title_canon_sha256":"fa097067d655901294f954b7e6cd951a0f24b28d22908268312bea9e4ba6b076"},"schema_version":"1.0","source":{"id":"2411.18957","kind":"arxiv","version":2}},"canonical_sha256":"fb61c7d4e2b8a02ca65cbaaf0e54c94a1449aaf76274006f6d33a3c01662a5b3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fb61c7d4e2b8a02ca65cbaaf0e54c94a1449aaf76274006f6d33a3c01662a5b3","first_computed_at":"2026-05-26T01:03:09.705488Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T01:03:09.705488Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Getlu7HzOJ/6lbVcJmj48xPWLiCMmCWoBamlXJS9qsFtaTi4uwuTnyEDWIsOjiazvXkruNhSEsTbS2rpBaS9AQ==","signature_status":"signed_v1","signed_at":"2026-05-26T01:03:09.706329Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.18957","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6dc00a31e925758170b77c669e03b281bc3a66201d309abed386f0ad19161fec","sha256:e94d0dde5300c5124f5fbd12f7cf2dcf7a815f846b887828fd8cb200f80d6ad0"],"state_sha256":"8957e61ab9cfcfb928981fed72e3d6a2f4a83b00f8caa1c728ceb1b6fd274d67"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G9ta2jHVwzVWvR8yRnC1SBXbhq8847cE5nKaGRLY/LeK+RUFzsKqdsJiS70h1ZtwMtiY5X/dPenlq5vrtvPjAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-01T17:19:58.497365Z","bundle_sha256":"52d5aaff4643313131d5721f1b676cdad948925f60718fcf34173d18a07aa720"}}