{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:AYZESI4YCMMTJL4BCSSAQPZN64","short_pith_number":"pith:AYZESI4Y","canonical_record":{"source":{"id":"1602.03572","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2016-02-10T23:24:46Z","cross_cats_sorted":[],"title_canon_sha256":"c80e99daae2a4aff13f17764b4d19705d57ded57b32c15f4d3d092fdd8ce8470","abstract_canon_sha256":"27a418ab2d99a078119bb5d643653fbde0b81f28914b852f0ee33d5d7481326b"},"schema_version":"1.0"},"canonical_sha256":"0632492398131934af8114a4083f2df73431845cee7d0a95c9c4116899a10118","source":{"kind":"arxiv","id":"1602.03572","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.03572","created_at":"2026-05-18T01:03:59Z"},{"alias_kind":"arxiv_version","alias_value":"1602.03572v5","created_at":"2026-05-18T01:03:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.03572","created_at":"2026-05-18T01:03:59Z"},{"alias_kind":"pith_short_12","alias_value":"AYZESI4YCMMT","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_16","alias_value":"AYZESI4YCMMTJL4B","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_8","alias_value":"AYZESI4Y","created_at":"2026-05-18T12:30:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:AYZESI4YCMMTJL4BCSSAQPZN64","target":"record","payload":{"canonical_record":{"source":{"id":"1602.03572","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2016-02-10T23:24:46Z","cross_cats_sorted":[],"title_canon_sha256":"c80e99daae2a4aff13f17764b4d19705d57ded57b32c15f4d3d092fdd8ce8470","abstract_canon_sha256":"27a418ab2d99a078119bb5d643653fbde0b81f28914b852f0ee33d5d7481326b"},"schema_version":"1.0"},"canonical_sha256":"0632492398131934af8114a4083f2df73431845cee7d0a95c9c4116899a10118","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:03:59.518290Z","signature_b64":"19jIYcUNywlJ1qkw7hkl3JZVnAtbsghwRRoWyND9iuygY2wIhIOn9dVaSdTaDjMEw1bIqkipMCrVTG0UCN2aAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0632492398131934af8114a4083f2df73431845cee7d0a95c9c4116899a10118","last_reissued_at":"2026-05-18T01:03:59.517521Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:03:59.517521Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1602.03572","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:03:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dC0OSjE1/qGjE4TE6VpCFr6Ed7S/DK3GFcXpxWiuOGVhL98MkZUW1xDcHMxfK8AnS81iI7KHbi+4Nhc89LLdCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T09:21:44.894865Z"},"content_sha256":"48a8ecf24dd9e2b41c8ab7ba5b3fc6115da59e2d55ce20b5d25a8dba6d3402e6","schema_version":"1.0","event_id":"sha256:48a8ecf24dd9e2b41c8ab7ba5b3fc6115da59e2d55ce20b5d25a8dba6d3402e6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:AYZESI4YCMMTJL4BCSSAQPZN64","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Effective Sample Size for Importance Sampling based on discrepancy measures","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"F. Louzada, L. Martino, V. Elvira","submitted_at":"2016-02-10T23:24:46Z","abstract_excerpt":"The Effective Sample Size (ESS) is an important measure of efficiency of Monte Carlo methods such as Markov Chain Monte Carlo (MCMC) and Importance Sampling (IS) techniques. In the IS context, an approximation $\\widehat{ESS}$ of the theoretical ESS definition is widely applied, involving the inverse of the sum of the squares of the normalized importance weights. This formula, $\\widehat{ESS}$, has become an essential piece within Sequential Monte Carlo (SMC) methods, to assess the convenience of a resampling step. From another perspective, the expression $\\widehat{ESS}$ is related to the Euclid"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.03572","kind":"arxiv","version":5},"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":"2026-05-18T01:03:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+r7G6lGUlA8GX7x1MFnUq/wWA/4KC9Tebj4l/BjgBqfJ9Q7hxyqghIUdzajOeRPKTZtjbmAxFp0fyQ+XspI6BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T09:21:44.895209Z"},"content_sha256":"3205f8df4a8967078a7d9c4308b4d87c0f04e12ea6994fb2a163c903458909b1","schema_version":"1.0","event_id":"sha256:3205f8df4a8967078a7d9c4308b4d87c0f04e12ea6994fb2a163c903458909b1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AYZESI4YCMMTJL4BCSSAQPZN64/bundle.json","state_url":"https://pith.science/pith/AYZESI4YCMMTJL4BCSSAQPZN64/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AYZESI4YCMMTJL4BCSSAQPZN64/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":"2026-06-27T09:21:44Z","links":{"resolver":"https://pith.science/pith/AYZESI4YCMMTJL4BCSSAQPZN64","bundle":"https://pith.science/pith/AYZESI4YCMMTJL4BCSSAQPZN64/bundle.json","state":"https://pith.science/pith/AYZESI4YCMMTJL4BCSSAQPZN64/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AYZESI4YCMMTJL4BCSSAQPZN64/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:AYZESI4YCMMTJL4BCSSAQPZN64","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":"27a418ab2d99a078119bb5d643653fbde0b81f28914b852f0ee33d5d7481326b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2016-02-10T23:24:46Z","title_canon_sha256":"c80e99daae2a4aff13f17764b4d19705d57ded57b32c15f4d3d092fdd8ce8470"},"schema_version":"1.0","source":{"id":"1602.03572","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.03572","created_at":"2026-05-18T01:03:59Z"},{"alias_kind":"arxiv_version","alias_value":"1602.03572v5","created_at":"2026-05-18T01:03:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.03572","created_at":"2026-05-18T01:03:59Z"},{"alias_kind":"pith_short_12","alias_value":"AYZESI4YCMMT","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_16","alias_value":"AYZESI4YCMMTJL4B","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_8","alias_value":"AYZESI4Y","created_at":"2026-05-18T12:30:07Z"}],"graph_snapshots":[{"event_id":"sha256:3205f8df4a8967078a7d9c4308b4d87c0f04e12ea6994fb2a163c903458909b1","target":"graph","created_at":"2026-05-18T01:03:59Z","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":"The Effective Sample Size (ESS) is an important measure of efficiency of Monte Carlo methods such as Markov Chain Monte Carlo (MCMC) and Importance Sampling (IS) techniques. In the IS context, an approximation $\\widehat{ESS}$ of the theoretical ESS definition is widely applied, involving the inverse of the sum of the squares of the normalized importance weights. This formula, $\\widehat{ESS}$, has become an essential piece within Sequential Monte Carlo (SMC) methods, to assess the convenience of a resampling step. From another perspective, the expression $\\widehat{ESS}$ is related to the Euclid","authors_text":"F. Louzada, L. Martino, V. Elvira","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2016-02-10T23:24:46Z","title":"Effective Sample Size for Importance Sampling based on discrepancy measures"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.03572","kind":"arxiv","version":5},"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":"sha256:48a8ecf24dd9e2b41c8ab7ba5b3fc6115da59e2d55ce20b5d25a8dba6d3402e6","target":"record","created_at":"2026-05-18T01:03:59Z","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":"27a418ab2d99a078119bb5d643653fbde0b81f28914b852f0ee33d5d7481326b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2016-02-10T23:24:46Z","title_canon_sha256":"c80e99daae2a4aff13f17764b4d19705d57ded57b32c15f4d3d092fdd8ce8470"},"schema_version":"1.0","source":{"id":"1602.03572","kind":"arxiv","version":5}},"canonical_sha256":"0632492398131934af8114a4083f2df73431845cee7d0a95c9c4116899a10118","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0632492398131934af8114a4083f2df73431845cee7d0a95c9c4116899a10118","first_computed_at":"2026-05-18T01:03:59.517521Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:03:59.517521Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"19jIYcUNywlJ1qkw7hkl3JZVnAtbsghwRRoWyND9iuygY2wIhIOn9dVaSdTaDjMEw1bIqkipMCrVTG0UCN2aAw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:03:59.518290Z","signed_message":"canonical_sha256_bytes"},"source_id":"1602.03572","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:48a8ecf24dd9e2b41c8ab7ba5b3fc6115da59e2d55ce20b5d25a8dba6d3402e6","sha256:3205f8df4a8967078a7d9c4308b4d87c0f04e12ea6994fb2a163c903458909b1"],"state_sha256":"3fbca710369a9e771dc319b61f78e1257ddfc591675d918d9002fc20aecad6a2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZBinncJcqCx6xLME8Fpg9k8YDOJ44z0yPiXzPtvfaT8mRbEKlaBNrDiYQbU1Q4JS8gB0TRcP4whMof1LuyVFDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T09:21:44.897061Z","bundle_sha256":"89b72c9583e88bebefba09287ed194cc60dc1079fb70abe5580537ab5d18bc2d"}}