{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:ACB4WHSSVTKHT4VZ7BWPTDAAOH","short_pith_number":"pith:ACB4WHSS","canonical_record":{"source":{"id":"1701.07263","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-01-25T11:05:20Z","cross_cats_sorted":[],"title_canon_sha256":"95c66334b0d7db49d0028f5328b66156a57db192fdb87760c6970ea9803dcd5b","abstract_canon_sha256":"6b37e3496c7b9b413c3a5df30df7d1ff5bdb7671afb0be4bd6b245b01e1f0f7f"},"schema_version":"1.0"},"canonical_sha256":"0083cb1e52acd479f2b9f86cf98c0071e5d795951c78d5c071ef5c74d564a281","source":{"kind":"arxiv","id":"1701.07263","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1701.07263","created_at":"2026-05-18T00:52:05Z"},{"alias_kind":"arxiv_version","alias_value":"1701.07263v1","created_at":"2026-05-18T00:52:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1701.07263","created_at":"2026-05-18T00:52:05Z"},{"alias_kind":"pith_short_12","alias_value":"ACB4WHSSVTKH","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_16","alias_value":"ACB4WHSSVTKHT4VZ","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_8","alias_value":"ACB4WHSS","created_at":"2026-05-18T12:31:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:ACB4WHSSVTKHT4VZ7BWPTDAAOH","target":"record","payload":{"canonical_record":{"source":{"id":"1701.07263","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-01-25T11:05:20Z","cross_cats_sorted":[],"title_canon_sha256":"95c66334b0d7db49d0028f5328b66156a57db192fdb87760c6970ea9803dcd5b","abstract_canon_sha256":"6b37e3496c7b9b413c3a5df30df7d1ff5bdb7671afb0be4bd6b245b01e1f0f7f"},"schema_version":"1.0"},"canonical_sha256":"0083cb1e52acd479f2b9f86cf98c0071e5d795951c78d5c071ef5c74d564a281","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:52:05.126103Z","signature_b64":"evX9vvEv6Xv6kDt6TxCGDIX+vmWXxh9hTGDIZ6ZCldAXgi2ONR22LolWsbhenUgoETVQ6s9sB+UFxFXTBzXyDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0083cb1e52acd479f2b9f86cf98c0071e5d795951c78d5c071ef5c74d564a281","last_reissued_at":"2026-05-18T00:52:05.125433Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:52:05.125433Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1701.07263","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":"2026-05-18T00:52:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1KilO4ihbf/jgVge8fr3XuFh+an5xDsfXxeVVFSpMrCXt19jSYKO9935E/6QaMhVb3ecwx/tOF9aJCA6F07ZBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T06:31:14.333096Z"},"content_sha256":"7bf54f1103a00f578f4fa12a41ba64e9ff35652fb1ed67fbf9ee625d38e9f36b","schema_version":"1.0","event_id":"sha256:7bf54f1103a00f578f4fa12a41ba64e9ff35652fb1ed67fbf9ee625d38e9f36b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:ACB4WHSSVTKHT4VZ7BWPTDAAOH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Likelihood ratio Haar variance stabilization and normalization for Poisson and other non-Gaussian noise removal","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Piotr Fryzlewicz","submitted_at":"2017-01-25T11:05:20Z","abstract_excerpt":"We propose a new methodology for denoising, variance-stabilizing and normalizing signals whose both mean and variance are parameterized by a single unknown varying parameter, such as Poisson or scaled chi-squared. Key to our methodology is the observation that the signed and square-rooted generalized log-likelihood ratio test for the equality of the local means is approximately and asymptotically distributed as standard normal under the null. We use these test statistics within the Haar wavelet transform at each scale and location, referring to them as the likelihood ratio Haar (LRH) coefficie"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1701.07263","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":"2026-05-18T00:52:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4aAAOLS/s2KprZFvNL90cBLXAjznXg1Y8EBUO8qP4hxzgacc5OhfUzDculHL85LXTGYoJ0a2Kxac4DVZ7WeXDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T06:31:14.333448Z"},"content_sha256":"ce27cd516c385c63f76669d17b3f207910bd3f196a1c81db127a2744dd333164","schema_version":"1.0","event_id":"sha256:ce27cd516c385c63f76669d17b3f207910bd3f196a1c81db127a2744dd333164"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ACB4WHSSVTKHT4VZ7BWPTDAAOH/bundle.json","state_url":"https://pith.science/pith/ACB4WHSSVTKHT4VZ7BWPTDAAOH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ACB4WHSSVTKHT4VZ7BWPTDAAOH/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":"2026-06-07T06:31:14Z","links":{"resolver":"https://pith.science/pith/ACB4WHSSVTKHT4VZ7BWPTDAAOH","bundle":"https://pith.science/pith/ACB4WHSSVTKHT4VZ7BWPTDAAOH/bundle.json","state":"https://pith.science/pith/ACB4WHSSVTKHT4VZ7BWPTDAAOH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ACB4WHSSVTKHT4VZ7BWPTDAAOH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:ACB4WHSSVTKHT4VZ7BWPTDAAOH","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":"6b37e3496c7b9b413c3a5df30df7d1ff5bdb7671afb0be4bd6b245b01e1f0f7f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-01-25T11:05:20Z","title_canon_sha256":"95c66334b0d7db49d0028f5328b66156a57db192fdb87760c6970ea9803dcd5b"},"schema_version":"1.0","source":{"id":"1701.07263","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1701.07263","created_at":"2026-05-18T00:52:05Z"},{"alias_kind":"arxiv_version","alias_value":"1701.07263v1","created_at":"2026-05-18T00:52:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1701.07263","created_at":"2026-05-18T00:52:05Z"},{"alias_kind":"pith_short_12","alias_value":"ACB4WHSSVTKH","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_16","alias_value":"ACB4WHSSVTKHT4VZ","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_8","alias_value":"ACB4WHSS","created_at":"2026-05-18T12:31:05Z"}],"graph_snapshots":[{"event_id":"sha256:ce27cd516c385c63f76669d17b3f207910bd3f196a1c81db127a2744dd333164","target":"graph","created_at":"2026-05-18T00:52:05Z","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 propose a new methodology for denoising, variance-stabilizing and normalizing signals whose both mean and variance are parameterized by a single unknown varying parameter, such as Poisson or scaled chi-squared. Key to our methodology is the observation that the signed and square-rooted generalized log-likelihood ratio test for the equality of the local means is approximately and asymptotically distributed as standard normal under the null. We use these test statistics within the Haar wavelet transform at each scale and location, referring to them as the likelihood ratio Haar (LRH) coefficie","authors_text":"Piotr Fryzlewicz","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-01-25T11:05:20Z","title":"Likelihood ratio Haar variance stabilization and normalization for Poisson and other non-Gaussian noise removal"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1701.07263","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":"sha256:7bf54f1103a00f578f4fa12a41ba64e9ff35652fb1ed67fbf9ee625d38e9f36b","target":"record","created_at":"2026-05-18T00:52:05Z","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":"6b37e3496c7b9b413c3a5df30df7d1ff5bdb7671afb0be4bd6b245b01e1f0f7f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-01-25T11:05:20Z","title_canon_sha256":"95c66334b0d7db49d0028f5328b66156a57db192fdb87760c6970ea9803dcd5b"},"schema_version":"1.0","source":{"id":"1701.07263","kind":"arxiv","version":1}},"canonical_sha256":"0083cb1e52acd479f2b9f86cf98c0071e5d795951c78d5c071ef5c74d564a281","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0083cb1e52acd479f2b9f86cf98c0071e5d795951c78d5c071ef5c74d564a281","first_computed_at":"2026-05-18T00:52:05.125433Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:52:05.125433Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"evX9vvEv6Xv6kDt6TxCGDIX+vmWXxh9hTGDIZ6ZCldAXgi2ONR22LolWsbhenUgoETVQ6s9sB+UFxFXTBzXyDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:52:05.126103Z","signed_message":"canonical_sha256_bytes"},"source_id":"1701.07263","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7bf54f1103a00f578f4fa12a41ba64e9ff35652fb1ed67fbf9ee625d38e9f36b","sha256:ce27cd516c385c63f76669d17b3f207910bd3f196a1c81db127a2744dd333164"],"state_sha256":"8bc347eb5fb27db9e569610b3df31fdaf767d891c5763d28169784feab5546c3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"97M1EfhvY76lHyBb9ecoGXjnx0OuGJ9ceXeyhrIRLiFoC/IbJ2drQyRJHKf56HMs6ek+E/9abeczCLGfgtWcBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T06:31:14.335447Z","bundle_sha256":"a54d0a59db62ffe0798ecb588e7b976d9277ac4045b0ef90ce7c1302aa5c5f66"}}