{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:NMR5STVTYTOPYUNCXD6GHBPKF7","short_pith_number":"pith:NMR5STVT","canonical_record":{"source":{"id":"2404.17812","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2024-04-27T07:33:32Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"3b0eb4e06486b8fc2f6472701bf76af84be0121a6f61e5cfaace5fdb4d3087bc","abstract_canon_sha256":"77e2e93990e44480e615c2546cdc0f168b38a17c4d0bc99cb6e8f7b8dd72701e"},"schema_version":"1.0"},"canonical_sha256":"6b23d94eb3c4dcfc51a2b8fc6385ea2ff14c6e3c450888ba33fc916e9cb0635e","source":{"kind":"arxiv","id":"2404.17812","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.17812","created_at":"2026-07-05T08:12:54Z"},{"alias_kind":"arxiv_version","alias_value":"2404.17812v1","created_at":"2026-07-05T08:12:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.17812","created_at":"2026-07-05T08:12:54Z"},{"alias_kind":"pith_short_12","alias_value":"NMR5STVTYTOP","created_at":"2026-07-05T08:12:54Z"},{"alias_kind":"pith_short_16","alias_value":"NMR5STVTYTOPYUNC","created_at":"2026-07-05T08:12:54Z"},{"alias_kind":"pith_short_8","alias_value":"NMR5STVT","created_at":"2026-07-05T08:12:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:NMR5STVTYTOPYUNCXD6GHBPKF7","target":"record","payload":{"canonical_record":{"source":{"id":"2404.17812","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2024-04-27T07:33:32Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"3b0eb4e06486b8fc2f6472701bf76af84be0121a6f61e5cfaace5fdb4d3087bc","abstract_canon_sha256":"77e2e93990e44480e615c2546cdc0f168b38a17c4d0bc99cb6e8f7b8dd72701e"},"schema_version":"1.0"},"canonical_sha256":"6b23d94eb3c4dcfc51a2b8fc6385ea2ff14c6e3c450888ba33fc916e9cb0635e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:12:54.458012Z","signature_b64":"trt66kjwJoXFxPBNqI++X1ju/XlQvsucHyx2PndetMKpkaij7djTtGZyw5QXaNgTAnnSlG8LUkxTA0Ip1srAAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6b23d94eb3c4dcfc51a2b8fc6385ea2ff14c6e3c450888ba33fc916e9cb0635e","last_reissued_at":"2026-07-05T08:12:54.457553Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:12:54.457553Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.17812","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":"2026-07-05T08:12:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NKmiM7qKL8DeBLfO5ESpq266w7ongQei3ci88E87rohXyXm2kXhHkMg4hiR22EvIDFEXd0ZhYgJJHAYgAf/8Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T09:38:24.011232Z"},"content_sha256":"64b66f88b037bfa783697329b102f7865f966a55e2dcbb478e92aa7323805db4","schema_version":"1.0","event_id":"sha256:64b66f88b037bfa783697329b102f7865f966a55e2dcbb478e92aa7323805db4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:NMR5STVTYTOPYUNCXD6GHBPKF7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"High-Dimensional Single-Index Models: Link Estimation and Marginal Inference","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ME","stat.TH"],"primary_cat":"math.ST","authors_text":"Kazuma Sawaya, Masaaki Imaizumi, Yoshimasa Uematsu","submitted_at":"2024-04-27T07:33:32Z","abstract_excerpt":"This study proposes a novel method for estimation and hypothesis testing in high-dimensional single-index models. We address a common scenario where the sample size and the dimension of regression coefficients are large and comparable. Unlike traditional approaches, which often overlook the estimation of the unknown link function, we introduce a new method for link function estimation. Leveraging the information from the estimated link function, we propose more efficient estimators that are better aligned with the underlying model. Furthermore, we rigorously establish the asymptotic normality "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.17812","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/2404.17812/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":"2026-07-05T08:12:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W46w8iT20xUpTO7b0SOfvuxUkheMuXJPu/hNrmM0qZ+60UcjJG/G0tsZsm/uUJ4KhuQPAvYrmLTNQdRyVJ2ABA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T09:38:24.011622Z"},"content_sha256":"9fd49bc7519cd69c62dd2c33f127cf36835cb1b3d2ec19665712d414b9195953","schema_version":"1.0","event_id":"sha256:9fd49bc7519cd69c62dd2c33f127cf36835cb1b3d2ec19665712d414b9195953"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NMR5STVTYTOPYUNCXD6GHBPKF7/bundle.json","state_url":"https://pith.science/pith/NMR5STVTYTOPYUNCXD6GHBPKF7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NMR5STVTYTOPYUNCXD6GHBPKF7/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":"2026-07-06T09:38:24Z","links":{"resolver":"https://pith.science/pith/NMR5STVTYTOPYUNCXD6GHBPKF7","bundle":"https://pith.science/pith/NMR5STVTYTOPYUNCXD6GHBPKF7/bundle.json","state":"https://pith.science/pith/NMR5STVTYTOPYUNCXD6GHBPKF7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NMR5STVTYTOPYUNCXD6GHBPKF7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NMR5STVTYTOPYUNCXD6GHBPKF7","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":"77e2e93990e44480e615c2546cdc0f168b38a17c4d0bc99cb6e8f7b8dd72701e","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2024-04-27T07:33:32Z","title_canon_sha256":"3b0eb4e06486b8fc2f6472701bf76af84be0121a6f61e5cfaace5fdb4d3087bc"},"schema_version":"1.0","source":{"id":"2404.17812","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.17812","created_at":"2026-07-05T08:12:54Z"},{"alias_kind":"arxiv_version","alias_value":"2404.17812v1","created_at":"2026-07-05T08:12:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.17812","created_at":"2026-07-05T08:12:54Z"},{"alias_kind":"pith_short_12","alias_value":"NMR5STVTYTOP","created_at":"2026-07-05T08:12:54Z"},{"alias_kind":"pith_short_16","alias_value":"NMR5STVTYTOPYUNC","created_at":"2026-07-05T08:12:54Z"},{"alias_kind":"pith_short_8","alias_value":"NMR5STVT","created_at":"2026-07-05T08:12:54Z"}],"graph_snapshots":[{"event_id":"sha256:9fd49bc7519cd69c62dd2c33f127cf36835cb1b3d2ec19665712d414b9195953","target":"graph","created_at":"2026-07-05T08:12:54Z","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/2404.17812/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study proposes a novel method for estimation and hypothesis testing in high-dimensional single-index models. We address a common scenario where the sample size and the dimension of regression coefficients are large and comparable. Unlike traditional approaches, which often overlook the estimation of the unknown link function, we introduce a new method for link function estimation. Leveraging the information from the estimated link function, we propose more efficient estimators that are better aligned with the underlying model. Furthermore, we rigorously establish the asymptotic normality ","authors_text":"Kazuma Sawaya, Masaaki Imaizumi, Yoshimasa Uematsu","cross_cats":["stat.ME","stat.TH"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2024-04-27T07:33:32Z","title":"High-Dimensional Single-Index Models: Link Estimation and Marginal Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.17812","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":"sha256:64b66f88b037bfa783697329b102f7865f966a55e2dcbb478e92aa7323805db4","target":"record","created_at":"2026-07-05T08:12:54Z","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":"77e2e93990e44480e615c2546cdc0f168b38a17c4d0bc99cb6e8f7b8dd72701e","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2024-04-27T07:33:32Z","title_canon_sha256":"3b0eb4e06486b8fc2f6472701bf76af84be0121a6f61e5cfaace5fdb4d3087bc"},"schema_version":"1.0","source":{"id":"2404.17812","kind":"arxiv","version":1}},"canonical_sha256":"6b23d94eb3c4dcfc51a2b8fc6385ea2ff14c6e3c450888ba33fc916e9cb0635e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6b23d94eb3c4dcfc51a2b8fc6385ea2ff14c6e3c450888ba33fc916e9cb0635e","first_computed_at":"2026-07-05T08:12:54.457553Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:12:54.457553Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"trt66kjwJoXFxPBNqI++X1ju/XlQvsucHyx2PndetMKpkaij7djTtGZyw5QXaNgTAnnSlG8LUkxTA0Ip1srAAw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:12:54.458012Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.17812","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:64b66f88b037bfa783697329b102f7865f966a55e2dcbb478e92aa7323805db4","sha256:9fd49bc7519cd69c62dd2c33f127cf36835cb1b3d2ec19665712d414b9195953"],"state_sha256":"83eaf1fa57d6358875d679ac7fd5b4f6f3744a190827e6e688aaa31db055a4fb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0Ugrx86XbMIrzSZpTZxTjsDFp2j0+nF+ba++3EPicv00Y2UNsYr1O9mvsmJDlvZXmT+cdHJF3UZJpK25obo+Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T09:38:24.013621Z","bundle_sha256":"9407ab981bbd3736f640c486c9b3a4fcf7e77f646677a3cc696567f3972a772a"}}