{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:Z3DQ5BQPPE5KLS4O2CF2Z4J5C7","short_pith_number":"pith:Z3DQ5BQP","canonical_record":{"source":{"id":"1310.3223","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2013-10-11T17:58:19Z","cross_cats_sorted":[],"title_canon_sha256":"a5caf583d2fb316f18c4c9b4fb56343213c7bb8b53d0f071eb9cea741c6b0005","abstract_canon_sha256":"c81b16ac6ed5e49125e84b1bd4b94740568db5d6e6000b4aac5796e8af0162e7"},"schema_version":"1.0"},"canonical_sha256":"cec70e860f793aa5cb8ed08bacf13d17fc134ef92aafb914bfd8aceb2b71b8b3","source":{"kind":"arxiv","id":"1310.3223","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1310.3223","created_at":"2026-05-18T03:10:44Z"},{"alias_kind":"arxiv_version","alias_value":"1310.3223v1","created_at":"2026-05-18T03:10:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1310.3223","created_at":"2026-05-18T03:10:44Z"},{"alias_kind":"pith_short_12","alias_value":"Z3DQ5BQPPE5K","created_at":"2026-05-18T12:28:09Z"},{"alias_kind":"pith_short_16","alias_value":"Z3DQ5BQPPE5KLS4O","created_at":"2026-05-18T12:28:09Z"},{"alias_kind":"pith_short_8","alias_value":"Z3DQ5BQP","created_at":"2026-05-18T12:28:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:Z3DQ5BQPPE5KLS4O2CF2Z4J5C7","target":"record","payload":{"canonical_record":{"source":{"id":"1310.3223","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2013-10-11T17:58:19Z","cross_cats_sorted":[],"title_canon_sha256":"a5caf583d2fb316f18c4c9b4fb56343213c7bb8b53d0f071eb9cea741c6b0005","abstract_canon_sha256":"c81b16ac6ed5e49125e84b1bd4b94740568db5d6e6000b4aac5796e8af0162e7"},"schema_version":"1.0"},"canonical_sha256":"cec70e860f793aa5cb8ed08bacf13d17fc134ef92aafb914bfd8aceb2b71b8b3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:10:44.584004Z","signature_b64":"8xEsMdUAKFaZ3C0M2iH71VPA7y6vrNWuFTwcL4vUDFh7kyBIex2J+R9+ffKAGr7ZyhQxMlypdkbWKisIC/64Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cec70e860f793aa5cb8ed08bacf13d17fc134ef92aafb914bfd8aceb2b71b8b3","last_reissued_at":"2026-05-18T03:10:44.583420Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:10:44.583420Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1310.3223","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:10:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sdPfBEWOiTJeNffbkkrDs72LS2h206KMzkacTje9+lL3jx8g+A5PogGV6BuNAOk1nNrPLSARbHDcknmJ2gIICA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T02:07:22.659897Z"},"content_sha256":"455b28979a83b73b6022fa95e5515479c47cba9c8dc643d55106b26819351119","schema_version":"1.0","event_id":"sha256:455b28979a83b73b6022fa95e5515479c47cba9c8dc643d55106b26819351119"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:Z3DQ5BQPPE5KLS4O2CF2Z4J5C7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sparse Median Graphs Estimation in a High Dimensional Semiparametric Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Brian Caffo, Fang Han, Han Liu","submitted_at":"2013-10-11T17:58:19Z","abstract_excerpt":"In this manuscript a unified framework for conducting inference on complex aggregated data in high dimensional settings is proposed. The data are assumed to be a collection of multiple non-Gaussian realizations with underlying undirected graphical structures. Utilizing the concept of median graphs in summarizing the commonality across these graphical structures, a novel semiparametric approach to modeling such complex aggregated data is provided along with robust estimation of the median graph, which is assumed to be sparse. The estimator is proved to be consistent in graph recovery and an upp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1310.3223","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:10:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tz53mXUT/IgYQKNXcXDKTMqXGzY9fVobMYqUP9TR5b07v4kFUPPDscy1nADwOUPc0tqCn2KGfq8nwytFkmu8DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T02:07:22.660564Z"},"content_sha256":"affbd54ef9e8b6524cf74da07122dd87c480292af60ae20b36ee7e5c9c8e11e5","schema_version":"1.0","event_id":"sha256:affbd54ef9e8b6524cf74da07122dd87c480292af60ae20b36ee7e5c9c8e11e5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Z3DQ5BQPPE5KLS4O2CF2Z4J5C7/bundle.json","state_url":"https://pith.science/pith/Z3DQ5BQPPE5KLS4O2CF2Z4J5C7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Z3DQ5BQPPE5KLS4O2CF2Z4J5C7/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":"2026-05-28T02:07:22Z","links":{"resolver":"https://pith.science/pith/Z3DQ5BQPPE5KLS4O2CF2Z4J5C7","bundle":"https://pith.science/pith/Z3DQ5BQPPE5KLS4O2CF2Z4J5C7/bundle.json","state":"https://pith.science/pith/Z3DQ5BQPPE5KLS4O2CF2Z4J5C7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Z3DQ5BQPPE5KLS4O2CF2Z4J5C7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:Z3DQ5BQPPE5KLS4O2CF2Z4J5C7","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":"c81b16ac6ed5e49125e84b1bd4b94740568db5d6e6000b4aac5796e8af0162e7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2013-10-11T17:58:19Z","title_canon_sha256":"a5caf583d2fb316f18c4c9b4fb56343213c7bb8b53d0f071eb9cea741c6b0005"},"schema_version":"1.0","source":{"id":"1310.3223","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1310.3223","created_at":"2026-05-18T03:10:44Z"},{"alias_kind":"arxiv_version","alias_value":"1310.3223v1","created_at":"2026-05-18T03:10:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1310.3223","created_at":"2026-05-18T03:10:44Z"},{"alias_kind":"pith_short_12","alias_value":"Z3DQ5BQPPE5K","created_at":"2026-05-18T12:28:09Z"},{"alias_kind":"pith_short_16","alias_value":"Z3DQ5BQPPE5KLS4O","created_at":"2026-05-18T12:28:09Z"},{"alias_kind":"pith_short_8","alias_value":"Z3DQ5BQP","created_at":"2026-05-18T12:28:09Z"}],"graph_snapshots":[{"event_id":"sha256:affbd54ef9e8b6524cf74da07122dd87c480292af60ae20b36ee7e5c9c8e11e5","target":"graph","created_at":"2026-05-18T03:10:44Z","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":"In this manuscript a unified framework for conducting inference on complex aggregated data in high dimensional settings is proposed. The data are assumed to be a collection of multiple non-Gaussian realizations with underlying undirected graphical structures. Utilizing the concept of median graphs in summarizing the commonality across these graphical structures, a novel semiparametric approach to modeling such complex aggregated data is provided along with robust estimation of the median graph, which is assumed to be sparse. The estimator is proved to be consistent in graph recovery and an upp","authors_text":"Brian Caffo, Fang Han, Han Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2013-10-11T17:58:19Z","title":"Sparse Median Graphs Estimation in a High Dimensional Semiparametric Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1310.3223","kind":"arxiv","version":1},"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":"sha256:455b28979a83b73b6022fa95e5515479c47cba9c8dc643d55106b26819351119","target":"record","created_at":"2026-05-18T03:10:44Z","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":"c81b16ac6ed5e49125e84b1bd4b94740568db5d6e6000b4aac5796e8af0162e7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2013-10-11T17:58:19Z","title_canon_sha256":"a5caf583d2fb316f18c4c9b4fb56343213c7bb8b53d0f071eb9cea741c6b0005"},"schema_version":"1.0","source":{"id":"1310.3223","kind":"arxiv","version":1}},"canonical_sha256":"cec70e860f793aa5cb8ed08bacf13d17fc134ef92aafb914bfd8aceb2b71b8b3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cec70e860f793aa5cb8ed08bacf13d17fc134ef92aafb914bfd8aceb2b71b8b3","first_computed_at":"2026-05-18T03:10:44.583420Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:10:44.583420Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8xEsMdUAKFaZ3C0M2iH71VPA7y6vrNWuFTwcL4vUDFh7kyBIex2J+R9+ffKAGr7ZyhQxMlypdkbWKisIC/64Cw==","signature_status":"signed_v1","signed_at":"2026-05-18T03:10:44.584004Z","signed_message":"canonical_sha256_bytes"},"source_id":"1310.3223","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:455b28979a83b73b6022fa95e5515479c47cba9c8dc643d55106b26819351119","sha256:affbd54ef9e8b6524cf74da07122dd87c480292af60ae20b36ee7e5c9c8e11e5"],"state_sha256":"4bff7f824ea997c0de8739e4bb2530ccdfbc9296e0dba1f204625dec80c7e1be"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cl5TQjrVdd7cMylycS0dFZwR97grhTUKlzkR53u+QnsUE+iU8e6Z84/ZnAalYh+ybLBx4Ebmh6j2ekLFZ6e8Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T02:07:22.663747Z","bundle_sha256":"be8d98766095fe1452fd5e1d47bf449d4acd2e0a7faa7f01f6b161836cb2b82d"}}