{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:I3FMNSCNQEXWN4VJFDEVSGRZZ7","short_pith_number":"pith:I3FMNSCN","schema_version":"1.0","canonical_sha256":"46cac6c84d812f66f2a928c9591a39cfc8ad9ccd232c7c2ab170b3dc604d9f21","source":{"kind":"arxiv","id":"2405.19637","version":2},"attestation_state":"computed","paper":{"title":"Inference in semiparametric formation models for directed networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.ST","stat.TH"],"primary_cat":"stat.ME","authors_text":"Lianqiang Qu, Lu Chen, Ting Yan, Yuguo Chen","submitted_at":"2024-05-30T02:42:27Z","abstract_excerpt":"We propose a semiparametric model for dyadic link formations in directed networks. The model contains a set of degree parameters that measure different effects of popularity or outgoingness across nodes, a regression parameter vector that reflects the homophily effect resulting from the nodal attributes or pairwise covariates associated with edges, and a set of latent random noises with unknown distributions. Our interest lies in inferring the unknown degree parameters and homophily parameters. The dimension of the degree parameters increases with the number of nodes. Under the high-dimensiona"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2405.19637","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2024-05-30T02:42:27Z","cross_cats_sorted":["math.ST","stat.TH"],"title_canon_sha256":"6d6229887782769463898843ec1995cbc6a23c775f14fe1e0fa86754f995eb81","abstract_canon_sha256":"e4f23a0b77da4caf41b0261fd1bbb87424b04fc31f0d9f7e8acb9fd9fb4547f3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:17:08.503300Z","signature_b64":"wD4mOr0l/gNYisiQJx8n5LcRDP7odwiweWp/1zXvbB9eP4+ilgJEUlyrvDvUnwC6k2JfS8yobnKtEIBR+2bOAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"46cac6c84d812f66f2a928c9591a39cfc8ad9ccd232c7c2ab170b3dc604d9f21","last_reissued_at":"2026-07-05T10:17:08.502828Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:17:08.502828Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Inference in semiparametric formation models for directed networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.ST","stat.TH"],"primary_cat":"stat.ME","authors_text":"Lianqiang Qu, Lu Chen, Ting Yan, Yuguo Chen","submitted_at":"2024-05-30T02:42:27Z","abstract_excerpt":"We propose a semiparametric model for dyadic link formations in directed networks. The model contains a set of degree parameters that measure different effects of popularity or outgoingness across nodes, a regression parameter vector that reflects the homophily effect resulting from the nodal attributes or pairwise covariates associated with edges, and a set of latent random noises with unknown distributions. Our interest lies in inferring the unknown degree parameters and homophily parameters. The dimension of the degree parameters increases with the number of nodes. Under the high-dimensiona"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.19637","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/2405.19637/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2405.19637","created_at":"2026-07-05T10:17:08.502882+00:00"},{"alias_kind":"arxiv_version","alias_value":"2405.19637v2","created_at":"2026-07-05T10:17:08.502882+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.19637","created_at":"2026-07-05T10:17:08.502882+00:00"},{"alias_kind":"pith_short_12","alias_value":"I3FMNSCNQEXW","created_at":"2026-07-05T10:17:08.502882+00:00"},{"alias_kind":"pith_short_16","alias_value":"I3FMNSCNQEXWN4VJ","created_at":"2026-07-05T10:17:08.502882+00:00"},{"alias_kind":"pith_short_8","alias_value":"I3FMNSCN","created_at":"2026-07-05T10:17:08.502882+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2410.23852","citing_title":"Bagging the Network","ref_index":55,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/I3FMNSCNQEXWN4VJFDEVSGRZZ7","json":"https://pith.science/pith/I3FMNSCNQEXWN4VJFDEVSGRZZ7.json","graph_json":"https://pith.science/api/pith-number/I3FMNSCNQEXWN4VJFDEVSGRZZ7/graph.json","events_json":"https://pith.science/api/pith-number/I3FMNSCNQEXWN4VJFDEVSGRZZ7/events.json","paper":"https://pith.science/paper/I3FMNSCN"},"agent_actions":{"view_html":"https://pith.science/pith/I3FMNSCNQEXWN4VJFDEVSGRZZ7","download_json":"https://pith.science/pith/I3FMNSCNQEXWN4VJFDEVSGRZZ7.json","view_paper":"https://pith.science/paper/I3FMNSCN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2405.19637&json=true","fetch_graph":"https://pith.science/api/pith-number/I3FMNSCNQEXWN4VJFDEVSGRZZ7/graph.json","fetch_events":"https://pith.science/api/pith-number/I3FMNSCNQEXWN4VJFDEVSGRZZ7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/I3FMNSCNQEXWN4VJFDEVSGRZZ7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/I3FMNSCNQEXWN4VJFDEVSGRZZ7/action/storage_attestation","attest_author":"https://pith.science/pith/I3FMNSCNQEXWN4VJFDEVSGRZZ7/action/author_attestation","sign_citation":"https://pith.science/pith/I3FMNSCNQEXWN4VJFDEVSGRZZ7/action/citation_signature","submit_replication":"https://pith.science/pith/I3FMNSCNQEXWN4VJFDEVSGRZZ7/action/replication_record"}},"created_at":"2026-07-05T10:17:08.502882+00:00","updated_at":"2026-07-05T10:17:08.502882+00:00"}