{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:Y4SU4KHBIP7YP4XFJDUTLTVQ3T","short_pith_number":"pith:Y4SU4KHB","canonical_record":{"source":{"id":"1809.06156","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-09-17T12:26:51Z","cross_cats_sorted":["q-bio.QM"],"title_canon_sha256":"931d7b29bc2fdada1c2bfe51a66924dee68c7a76f9410ed113361605985214ee","abstract_canon_sha256":"025063d3b34f8f32b53007f6562f2003817d2b1d435cf971d211b2079ef0aa00"},"schema_version":"1.0"},"canonical_sha256":"c7254e28e143ff87f2e548e935ceb0dcec8c13cda7731798918ef608f54780f0","source":{"kind":"arxiv","id":"1809.06156","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.06156","created_at":"2026-05-17T23:47:12Z"},{"alias_kind":"arxiv_version","alias_value":"1809.06156v2","created_at":"2026-05-17T23:47:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.06156","created_at":"2026-05-17T23:47:12Z"},{"alias_kind":"pith_short_12","alias_value":"Y4SU4KHBIP7Y","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"Y4SU4KHBIP7YP4XF","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"Y4SU4KHB","created_at":"2026-05-18T12:33:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:Y4SU4KHBIP7YP4XFJDUTLTVQ3T","target":"record","payload":{"canonical_record":{"source":{"id":"1809.06156","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-09-17T12:26:51Z","cross_cats_sorted":["q-bio.QM"],"title_canon_sha256":"931d7b29bc2fdada1c2bfe51a66924dee68c7a76f9410ed113361605985214ee","abstract_canon_sha256":"025063d3b34f8f32b53007f6562f2003817d2b1d435cf971d211b2079ef0aa00"},"schema_version":"1.0"},"canonical_sha256":"c7254e28e143ff87f2e548e935ceb0dcec8c13cda7731798918ef608f54780f0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:12.510688Z","signature_b64":"QIHdRBra3tHkELH2S6qSDxLYuWgRjf/tcJnK8GDhWWV0WWakvLbTAVB7HrAnQyeZf3N7NcqPOyXJadVmPMuDBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c7254e28e143ff87f2e548e935ceb0dcec8c13cda7731798918ef608f54780f0","last_reissued_at":"2026-05-17T23:47:12.510011Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:12.510011Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.06156","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":"2026-05-17T23:47:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pjYMzd1eeTqz7EHBvD9H3ET8+8PGXpTqcMNMU5fhjJ6RHbm1Up9HEvDPWznXjnfCyfXn0XG9yW/AGkLOTOn1DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T18:01:08.284967Z"},"content_sha256":"4d2b3417e96e0612218e8b07d786d080a30e454b0dee04f984f80f77f715c866","schema_version":"1.0","event_id":"sha256:4d2b3417e96e0612218e8b07d786d080a30e454b0dee04f984f80f77f715c866"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:Y4SU4KHBIP7YP4XFJDUTLTVQ3T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Convex Formulation for Regularized Estimation of Structural Equation Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-bio.QM"],"primary_cat":"math.OC","authors_text":"Anupon Pruttiakaravanich, Jitkomut Songsiri","submitted_at":"2018-09-17T12:26:51Z","abstract_excerpt":"Path analysis is a model class of structural equation modeling (SEM), which it describes causal relations among measured variables in the form of a multiple linear regression. This paper presents two estimation formulations, one each for confirmatory and exploratory SEM, where a zero pattern of the estimated path coefficient matrix can explain a causality structure of the variables. The original nonlinear equality constraints of the model parameters were relaxed to an inequality, allowing the transformation of the original problem into a convex framework. A regularized estimation formulation w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.06156","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":"2026-05-17T23:47:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QLFtE1uaEyHmEQo8w5oU+NgLw+f9SWDksjaAMibrKSFFWzir1VGeksd0AQjl3I5//1VP1K8KeOw793hGJ54BCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T18:01:08.285626Z"},"content_sha256":"14c5e19dac496e0076a8d4cb9239c5f1f912f899f6527f02a42457a5c129e78d","schema_version":"1.0","event_id":"sha256:14c5e19dac496e0076a8d4cb9239c5f1f912f899f6527f02a42457a5c129e78d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y4SU4KHBIP7YP4XFJDUTLTVQ3T/bundle.json","state_url":"https://pith.science/pith/Y4SU4KHBIP7YP4XFJDUTLTVQ3T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y4SU4KHBIP7YP4XFJDUTLTVQ3T/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":"2026-06-08T18:01:08Z","links":{"resolver":"https://pith.science/pith/Y4SU4KHBIP7YP4XFJDUTLTVQ3T","bundle":"https://pith.science/pith/Y4SU4KHBIP7YP4XFJDUTLTVQ3T/bundle.json","state":"https://pith.science/pith/Y4SU4KHBIP7YP4XFJDUTLTVQ3T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y4SU4KHBIP7YP4XFJDUTLTVQ3T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:Y4SU4KHBIP7YP4XFJDUTLTVQ3T","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":"025063d3b34f8f32b53007f6562f2003817d2b1d435cf971d211b2079ef0aa00","cross_cats_sorted":["q-bio.QM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-09-17T12:26:51Z","title_canon_sha256":"931d7b29bc2fdada1c2bfe51a66924dee68c7a76f9410ed113361605985214ee"},"schema_version":"1.0","source":{"id":"1809.06156","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.06156","created_at":"2026-05-17T23:47:12Z"},{"alias_kind":"arxiv_version","alias_value":"1809.06156v2","created_at":"2026-05-17T23:47:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.06156","created_at":"2026-05-17T23:47:12Z"},{"alias_kind":"pith_short_12","alias_value":"Y4SU4KHBIP7Y","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"Y4SU4KHBIP7YP4XF","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"Y4SU4KHB","created_at":"2026-05-18T12:33:04Z"}],"graph_snapshots":[{"event_id":"sha256:14c5e19dac496e0076a8d4cb9239c5f1f912f899f6527f02a42457a5c129e78d","target":"graph","created_at":"2026-05-17T23:47:12Z","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":"Path analysis is a model class of structural equation modeling (SEM), which it describes causal relations among measured variables in the form of a multiple linear regression. This paper presents two estimation formulations, one each for confirmatory and exploratory SEM, where a zero pattern of the estimated path coefficient matrix can explain a causality structure of the variables. The original nonlinear equality constraints of the model parameters were relaxed to an inequality, allowing the transformation of the original problem into a convex framework. A regularized estimation formulation w","authors_text":"Anupon Pruttiakaravanich, Jitkomut Songsiri","cross_cats":["q-bio.QM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-09-17T12:26:51Z","title":"Convex Formulation for Regularized Estimation of Structural Equation Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.06156","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":"sha256:4d2b3417e96e0612218e8b07d786d080a30e454b0dee04f984f80f77f715c866","target":"record","created_at":"2026-05-17T23:47:12Z","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":"025063d3b34f8f32b53007f6562f2003817d2b1d435cf971d211b2079ef0aa00","cross_cats_sorted":["q-bio.QM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-09-17T12:26:51Z","title_canon_sha256":"931d7b29bc2fdada1c2bfe51a66924dee68c7a76f9410ed113361605985214ee"},"schema_version":"1.0","source":{"id":"1809.06156","kind":"arxiv","version":2}},"canonical_sha256":"c7254e28e143ff87f2e548e935ceb0dcec8c13cda7731798918ef608f54780f0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c7254e28e143ff87f2e548e935ceb0dcec8c13cda7731798918ef608f54780f0","first_computed_at":"2026-05-17T23:47:12.510011Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:47:12.510011Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QIHdRBra3tHkELH2S6qSDxLYuWgRjf/tcJnK8GDhWWV0WWakvLbTAVB7HrAnQyeZf3N7NcqPOyXJadVmPMuDBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:47:12.510688Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.06156","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4d2b3417e96e0612218e8b07d786d080a30e454b0dee04f984f80f77f715c866","sha256:14c5e19dac496e0076a8d4cb9239c5f1f912f899f6527f02a42457a5c129e78d"],"state_sha256":"7bdaeee0973d0ea1bfdf9226f8a8535216c752ce3311ca97fe4f1c9ee98fc5e2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QxZI/sAnXZg9bcsXU1+2st1aGW03dkS4D3HcCffgfzIpfm6iXCBVeAp20QYrmffjjOgciXqb++jOR2E8Y+PGDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T18:01:08.289252Z","bundle_sha256":"0f0c05b06adf27a7f7a04635103f7fd96cfd2965baeae37d867a449f862cff22"}}