{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:HTYRTY7JDAMFCWS2B7XD6YDA2F","short_pith_number":"pith:HTYRTY7J","canonical_record":{"source":{"id":"1411.1440","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2014-11-05T22:45:45Z","cross_cats_sorted":[],"title_canon_sha256":"30006f36e151aaee31ca9d0b9d5623c9659d438935cc7f89dd7c476a22621b5e","abstract_canon_sha256":"e2e9c2f3913adedf18fb7ee8b65dc85d6393b1f885f6285215f154fffbd76a78"},"schema_version":"1.0"},"canonical_sha256":"3cf119e3e91818515a5a0fee3f6060d149d31aabd05858ad183e3e244c45de42","source":{"kind":"arxiv","id":"1411.1440","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1411.1440","created_at":"2026-05-18T02:38:27Z"},{"alias_kind":"arxiv_version","alias_value":"1411.1440v1","created_at":"2026-05-18T02:38:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1411.1440","created_at":"2026-05-18T02:38:27Z"},{"alias_kind":"pith_short_12","alias_value":"HTYRTY7JDAMF","created_at":"2026-05-18T12:28:30Z"},{"alias_kind":"pith_short_16","alias_value":"HTYRTY7JDAMFCWS2","created_at":"2026-05-18T12:28:30Z"},{"alias_kind":"pith_short_8","alias_value":"HTYRTY7J","created_at":"2026-05-18T12:28:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:HTYRTY7JDAMFCWS2B7XD6YDA2F","target":"record","payload":{"canonical_record":{"source":{"id":"1411.1440","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2014-11-05T22:45:45Z","cross_cats_sorted":[],"title_canon_sha256":"30006f36e151aaee31ca9d0b9d5623c9659d438935cc7f89dd7c476a22621b5e","abstract_canon_sha256":"e2e9c2f3913adedf18fb7ee8b65dc85d6393b1f885f6285215f154fffbd76a78"},"schema_version":"1.0"},"canonical_sha256":"3cf119e3e91818515a5a0fee3f6060d149d31aabd05858ad183e3e244c45de42","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:38:27.980019Z","signature_b64":"PXAOeEhQMoE035xiToPOPWn51t6K8j+c/8SxEvj2OMDkOCpGzKcuNzkBRyIzEfC5DW7WfNh93OBWdVnQgRljAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3cf119e3e91818515a5a0fee3f6060d149d31aabd05858ad183e3e244c45de42","last_reissued_at":"2026-05-18T02:38:27.979391Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:38:27.979391Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1411.1440","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":"2026-05-18T02:38:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LslsbfzGhPYh87lZqg+J9JW7V71CLcBiGXj4iQA+ehRnQ46K6YEzp9fS2O7Ubr1BJER8LfOIi/uvpwOjb0MaCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T20:06:17.742351Z"},"content_sha256":"d5f5e28c17a2460103ef51ff21e0aadbb3048af52267703a16d1e37362271d3a","schema_version":"1.0","event_id":"sha256:d5f5e28c17a2460103ef51ff21e0aadbb3048af52267703a16d1e37362271d3a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:HTYRTY7JDAMFCWS2B7XD6YDA2F","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sequential Joint Detection and Estimation: Optimum Tests and Applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Shang Li, Xiaodong Wang, Yasin Yilmaz","submitted_at":"2014-11-05T22:45:45Z","abstract_excerpt":"We treat the statistical inference problems in which one needs to detect and estimate simultaneously using as small number of samples as possible. Conventional methods treat the detection and estimation subproblems separately, ignoring the intrinsic coupling between them. However, a joint detection and estimation problem should be solved to maximize the overall performance. We address the sample size concern through a sequential and Bayesian setup. Specifically, we seek the optimum triplet of stopping time, detector, and estimator(s) that minimizes the number of samples subject to a constraint"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1411.1440","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":"2026-05-18T02:38:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9KdqMzXong0svoKipCDstMnUnc2A3V29B8X/9n4ufi42guILMbpWnToGezNuJ0gPApl2LNhA+n5k2oFvC2f8AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T20:06:17.742713Z"},"content_sha256":"9de97ba74ceb5be51d5075efbd2ba69de46d0598879ad61fb9fe48d4e2d35990","schema_version":"1.0","event_id":"sha256:9de97ba74ceb5be51d5075efbd2ba69de46d0598879ad61fb9fe48d4e2d35990"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HTYRTY7JDAMFCWS2B7XD6YDA2F/bundle.json","state_url":"https://pith.science/pith/HTYRTY7JDAMFCWS2B7XD6YDA2F/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HTYRTY7JDAMFCWS2B7XD6YDA2F/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":"2026-06-04T20:06:17Z","links":{"resolver":"https://pith.science/pith/HTYRTY7JDAMFCWS2B7XD6YDA2F","bundle":"https://pith.science/pith/HTYRTY7JDAMFCWS2B7XD6YDA2F/bundle.json","state":"https://pith.science/pith/HTYRTY7JDAMFCWS2B7XD6YDA2F/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HTYRTY7JDAMFCWS2B7XD6YDA2F/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:HTYRTY7JDAMFCWS2B7XD6YDA2F","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":"e2e9c2f3913adedf18fb7ee8b65dc85d6393b1f885f6285215f154fffbd76a78","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2014-11-05T22:45:45Z","title_canon_sha256":"30006f36e151aaee31ca9d0b9d5623c9659d438935cc7f89dd7c476a22621b5e"},"schema_version":"1.0","source":{"id":"1411.1440","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1411.1440","created_at":"2026-05-18T02:38:27Z"},{"alias_kind":"arxiv_version","alias_value":"1411.1440v1","created_at":"2026-05-18T02:38:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1411.1440","created_at":"2026-05-18T02:38:27Z"},{"alias_kind":"pith_short_12","alias_value":"HTYRTY7JDAMF","created_at":"2026-05-18T12:28:30Z"},{"alias_kind":"pith_short_16","alias_value":"HTYRTY7JDAMFCWS2","created_at":"2026-05-18T12:28:30Z"},{"alias_kind":"pith_short_8","alias_value":"HTYRTY7J","created_at":"2026-05-18T12:28:30Z"}],"graph_snapshots":[{"event_id":"sha256:9de97ba74ceb5be51d5075efbd2ba69de46d0598879ad61fb9fe48d4e2d35990","target":"graph","created_at":"2026-05-18T02:38:27Z","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":"We treat the statistical inference problems in which one needs to detect and estimate simultaneously using as small number of samples as possible. Conventional methods treat the detection and estimation subproblems separately, ignoring the intrinsic coupling between them. However, a joint detection and estimation problem should be solved to maximize the overall performance. We address the sample size concern through a sequential and Bayesian setup. Specifically, we seek the optimum triplet of stopping time, detector, and estimator(s) that minimizes the number of samples subject to a constraint","authors_text":"Shang Li, Xiaodong Wang, Yasin Yilmaz","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2014-11-05T22:45:45Z","title":"Sequential Joint Detection and Estimation: Optimum Tests and Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1411.1440","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:d5f5e28c17a2460103ef51ff21e0aadbb3048af52267703a16d1e37362271d3a","target":"record","created_at":"2026-05-18T02:38:27Z","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":"e2e9c2f3913adedf18fb7ee8b65dc85d6393b1f885f6285215f154fffbd76a78","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2014-11-05T22:45:45Z","title_canon_sha256":"30006f36e151aaee31ca9d0b9d5623c9659d438935cc7f89dd7c476a22621b5e"},"schema_version":"1.0","source":{"id":"1411.1440","kind":"arxiv","version":1}},"canonical_sha256":"3cf119e3e91818515a5a0fee3f6060d149d31aabd05858ad183e3e244c45de42","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3cf119e3e91818515a5a0fee3f6060d149d31aabd05858ad183e3e244c45de42","first_computed_at":"2026-05-18T02:38:27.979391Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:38:27.979391Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PXAOeEhQMoE035xiToPOPWn51t6K8j+c/8SxEvj2OMDkOCpGzKcuNzkBRyIzEfC5DW7WfNh93OBWdVnQgRljAg==","signature_status":"signed_v1","signed_at":"2026-05-18T02:38:27.980019Z","signed_message":"canonical_sha256_bytes"},"source_id":"1411.1440","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d5f5e28c17a2460103ef51ff21e0aadbb3048af52267703a16d1e37362271d3a","sha256:9de97ba74ceb5be51d5075efbd2ba69de46d0598879ad61fb9fe48d4e2d35990"],"state_sha256":"a3380fe719008f9dcaae8da89598704ac4e75f752567f743310403ef30c120b3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8D4PoygOeJt9VDDBuFQ2rKD6jVX6uWSl1Q+an8mGkv62UFaNgNx6k0XG+Gjn+Mlus6RQ4LPiQr0iAdFUNuD9Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T20:06:17.744741Z","bundle_sha256":"1517edd5ba5bad24ce33d41aaba6cbf75ebfb756a8ea29829bf398b71f9d8784"}}