{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:H6QER6DW6OU3XJDE4AQIRRI53M","short_pith_number":"pith:H6QER6DW","schema_version":"1.0","canonical_sha256":"3fa048f876f3a9bba464e02088c51ddb1ac85c90c8223c7dd8fd13655161cb2e","source":{"kind":"arxiv","id":"2302.08097","version":1},"attestation_state":"computed","paper":{"title":"New $\\sqrt{n}$-consistent, numerically stable higher-order influence function estimators","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["econ.EM","stat.ME","stat.ML","stat.TH"],"primary_cat":"math.ST","authors_text":"Chang Li, Lin Liu","submitted_at":"2023-02-16T05:25:21Z","abstract_excerpt":"Higher-Order Influence Functions (HOIFs) provide a unified theory for constructing rate-optimal estimators for a large class of low-dimensional (smooth) statistical functionals/parameters (and sometimes even infinite-dimensional functions) that arise in substantive fields including epidemiology, economics, and the social sciences. Since the introduction of HOIFs by Robins et al. (2008), they have been viewed mostly as a theoretical benchmark rather than a useful tool for statistical practice. Works aimed to flip the script are scant, but a few recent papers Liu et al. (2017, 2021b) make some p"},"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":"2302.08097","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2023-02-16T05:25:21Z","cross_cats_sorted":["econ.EM","stat.ME","stat.ML","stat.TH"],"title_canon_sha256":"c64f6feb258fb6e645d53157dd47aac2712cc7773826d6fe91e705887afb3c45","abstract_canon_sha256":"5e67e221a5a260376c68d645652914283663157a0c78d73d198ae4f1e0ac4b49"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:42:34.322823Z","signature_b64":"6PK2VsWsCKEf94cX2HP2sy1E5TkJHQClM0r/yZDyjKuwEFIT07F8hKmR+qHstGCytElQ1sdy4MVW5EcaQKohAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3fa048f876f3a9bba464e02088c51ddb1ac85c90c8223c7dd8fd13655161cb2e","last_reissued_at":"2026-07-05T05:42:34.322393Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:42:34.322393Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"New $\\sqrt{n}$-consistent, numerically stable higher-order influence function estimators","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["econ.EM","stat.ME","stat.ML","stat.TH"],"primary_cat":"math.ST","authors_text":"Chang Li, Lin Liu","submitted_at":"2023-02-16T05:25:21Z","abstract_excerpt":"Higher-Order Influence Functions (HOIFs) provide a unified theory for constructing rate-optimal estimators for a large class of low-dimensional (smooth) statistical functionals/parameters (and sometimes even infinite-dimensional functions) that arise in substantive fields including epidemiology, economics, and the social sciences. Since the introduction of HOIFs by Robins et al. (2008), they have been viewed mostly as a theoretical benchmark rather than a useful tool for statistical practice. Works aimed to flip the script are scant, but a few recent papers Liu et al. (2017, 2021b) make some p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.08097","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2302.08097/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":"2302.08097","created_at":"2026-07-05T05:42:34.322458+00:00"},{"alias_kind":"arxiv_version","alias_value":"2302.08097v1","created_at":"2026-07-05T05:42:34.322458+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.08097","created_at":"2026-07-05T05:42:34.322458+00:00"},{"alias_kind":"pith_short_12","alias_value":"H6QER6DW6OU3","created_at":"2026-07-05T05:42:34.322458+00:00"},{"alias_kind":"pith_short_16","alias_value":"H6QER6DW6OU3XJDE","created_at":"2026-07-05T05:42:34.322458+00:00"},{"alias_kind":"pith_short_8","alias_value":"H6QER6DW","created_at":"2026-07-05T05:42:34.322458+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/H6QER6DW6OU3XJDE4AQIRRI53M","json":"https://pith.science/pith/H6QER6DW6OU3XJDE4AQIRRI53M.json","graph_json":"https://pith.science/api/pith-number/H6QER6DW6OU3XJDE4AQIRRI53M/graph.json","events_json":"https://pith.science/api/pith-number/H6QER6DW6OU3XJDE4AQIRRI53M/events.json","paper":"https://pith.science/paper/H6QER6DW"},"agent_actions":{"view_html":"https://pith.science/pith/H6QER6DW6OU3XJDE4AQIRRI53M","download_json":"https://pith.science/pith/H6QER6DW6OU3XJDE4AQIRRI53M.json","view_paper":"https://pith.science/paper/H6QER6DW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2302.08097&json=true","fetch_graph":"https://pith.science/api/pith-number/H6QER6DW6OU3XJDE4AQIRRI53M/graph.json","fetch_events":"https://pith.science/api/pith-number/H6QER6DW6OU3XJDE4AQIRRI53M/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/H6QER6DW6OU3XJDE4AQIRRI53M/action/timestamp_anchor","attest_storage":"https://pith.science/pith/H6QER6DW6OU3XJDE4AQIRRI53M/action/storage_attestation","attest_author":"https://pith.science/pith/H6QER6DW6OU3XJDE4AQIRRI53M/action/author_attestation","sign_citation":"https://pith.science/pith/H6QER6DW6OU3XJDE4AQIRRI53M/action/citation_signature","submit_replication":"https://pith.science/pith/H6QER6DW6OU3XJDE4AQIRRI53M/action/replication_record"}},"created_at":"2026-07-05T05:42:34.322458+00:00","updated_at":"2026-07-05T05:42:34.322458+00:00"}