{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:HEENPH3STPO64NQMD4FYZANS6W","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":"487a6ec3cbb6befc198e5cf58c203ce4dadc66e6428d229d38a4c0d337da0a36","cross_cats_sorted":["stat.CO","stat.ME","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2019-07-25T14:58:07Z","title_canon_sha256":"6cd56cba3fc10c54d1092337c68e2878f993154a997cf0f64f2106e43a40e16b"},"schema_version":"1.0","source":{"id":"1907.11541","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.11541","created_at":"2026-07-05T00:16:20Z"},{"alias_kind":"arxiv_version","alias_value":"1907.11541v3","created_at":"2026-07-05T00:16:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.11541","created_at":"2026-07-05T00:16:20Z"},{"alias_kind":"pith_short_12","alias_value":"HEENPH3STPO6","created_at":"2026-07-05T00:16:20Z"},{"alias_kind":"pith_short_16","alias_value":"HEENPH3STPO64NQM","created_at":"2026-07-05T00:16:20Z"},{"alias_kind":"pith_short_8","alias_value":"HEENPH3S","created_at":"2026-07-05T00:16:20Z"}],"graph_snapshots":[{"event_id":"sha256:57fc11089201d09c68447165d977d5b2a2caca29a0a3f7d4609279b1d98d03ae","target":"graph","created_at":"2026-07-05T00:16:20Z","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/1907.11541/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"An important challenge in statistical analysis concerns the control of the finite sample bias of estimators. For example, the maximum likelihood estimator has a bias that can result in a significant inferential loss. This problem is typically magnified in high-dimensional settings where the number of variables $p$ is allowed to diverge with the sample size $n$. However, it is generally difficult to establish whether an estimator is unbiased and therefore its asymptotic order is a common approach used (in low-dimensional settings) to quantify the magnitude of the bias. As an alternative, we int","authors_text":"Maria-Pia Victoria-Feser, Mucyo Karemera, Samuel Orso, St\\'ephane Guerrier","cross_cats":["stat.CO","stat.ME","stat.TH"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2019-07-25T14:58:07Z","title":"Phase Transition Unbiased Estimation in High Dimensional Settings"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.11541","kind":"arxiv","version":3},"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":"sha256:18fb1fa399d845c5377314949207030740713e3faf3d8c1b0b4d95c5ffd10af7","target":"record","created_at":"2026-07-05T00:16:20Z","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":"487a6ec3cbb6befc198e5cf58c203ce4dadc66e6428d229d38a4c0d337da0a36","cross_cats_sorted":["stat.CO","stat.ME","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2019-07-25T14:58:07Z","title_canon_sha256":"6cd56cba3fc10c54d1092337c68e2878f993154a997cf0f64f2106e43a40e16b"},"schema_version":"1.0","source":{"id":"1907.11541","kind":"arxiv","version":3}},"canonical_sha256":"3908d79f729bddee360c1f0b8c81b2f59296922fef8d013d9e33406317d7e5a3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3908d79f729bddee360c1f0b8c81b2f59296922fef8d013d9e33406317d7e5a3","first_computed_at":"2026-07-05T00:16:20.908940Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:16:20.908940Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"R/m31OnDbD6MieMOVCSThHAdPiA33nhbV9+Z2AE+3T5PFNu6IRkCYK8WgVscZSdTVNseFMa6wRWL7vXX+oiUBg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:16:20.909421Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.11541","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:18fb1fa399d845c5377314949207030740713e3faf3d8c1b0b4d95c5ffd10af7","sha256:57fc11089201d09c68447165d977d5b2a2caca29a0a3f7d4609279b1d98d03ae"],"state_sha256":"20f2540f8a3bd04d4804ecb4b53f625aa5e02c93696217a76f1e595d43195d72"}