{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:6IWD2J63SQEFHVNBBSIJ6XLHHP","short_pith_number":"pith:6IWD2J63","canonical_record":{"source":{"id":"1202.6485","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2012-02-29T08:50:09Z","cross_cats_sorted":[],"title_canon_sha256":"7185edfed01e9eefa08279d363e5a9ae3d419690df4f46a622112c0d9edecc9f","abstract_canon_sha256":"eeeafcf0163042426ad1254f3e1c7d8ea7f9fb9a379d85b00df26147c0fbb2f0"},"schema_version":"1.0"},"canonical_sha256":"f22c3d27db940853d5a10c909f5d673bf449985bde07dd571980d074ab341748","source":{"kind":"arxiv","id":"1202.6485","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1202.6485","created_at":"2026-05-18T04:01:12Z"},{"alias_kind":"arxiv_version","alias_value":"1202.6485v1","created_at":"2026-05-18T04:01:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1202.6485","created_at":"2026-05-18T04:01:12Z"},{"alias_kind":"pith_short_12","alias_value":"6IWD2J63SQEF","created_at":"2026-05-18T12:26:56Z"},{"alias_kind":"pith_short_16","alias_value":"6IWD2J63SQEFHVNB","created_at":"2026-05-18T12:26:56Z"},{"alias_kind":"pith_short_8","alias_value":"6IWD2J63","created_at":"2026-05-18T12:26:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:6IWD2J63SQEFHVNBBSIJ6XLHHP","target":"record","payload":{"canonical_record":{"source":{"id":"1202.6485","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2012-02-29T08:50:09Z","cross_cats_sorted":[],"title_canon_sha256":"7185edfed01e9eefa08279d363e5a9ae3d419690df4f46a622112c0d9edecc9f","abstract_canon_sha256":"eeeafcf0163042426ad1254f3e1c7d8ea7f9fb9a379d85b00df26147c0fbb2f0"},"schema_version":"1.0"},"canonical_sha256":"f22c3d27db940853d5a10c909f5d673bf449985bde07dd571980d074ab341748","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:01:12.415103Z","signature_b64":"RQGY3rolLtn0E8NpFR6woMdMaBFR6RYynobLbSQKyFUINoSTKYzSAKy4S4UHJCXsQxi719rS7Mz6g9h9uVECDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f22c3d27db940853d5a10c909f5d673bf449985bde07dd571980d074ab341748","last_reissued_at":"2026-05-18T04:01:12.414207Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:01:12.414207Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1202.6485","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":"2026-05-18T04:01:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5ZoglT4xEXihwD2/y4r+eyJvl9gk3cOTPsC079f/drAM8Z88E/SjzQ1RXfus+uvS0AKwM+C5+h+/UAXliAkDBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T11:46:17.504629Z"},"content_sha256":"b4eba01529ed353a7c56babb6acf02319b0964aa22866084d055f9d53a314bdb","schema_version":"1.0","event_id":"sha256:b4eba01529ed353a7c56babb6acf02319b0964aa22866084d055f9d53a314bdb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:6IWD2J63SQEFHVNBBSIJ6XLHHP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Revisiting Guerry's data: Introducing spatial constraints in multivariate analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"St\\'ephane Dray, Thibaut Jombart","submitted_at":"2012-02-29T08:50:09Z","abstract_excerpt":"Standard multivariate analysis methods aim to identify and summarize the main structures in large data sets containing the description of a number of observations by several variables. In many cases, spatial information is also available for each observation, so that a map can be associated to the multivariate data set. Two main objectives are relevant in the analysis of spatial multivariate data: summarizing covariation structures and identifying spatial patterns. In practice, achieving both goals simultaneously is a statistical challenge, and a range of methods have been developed that offer"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1202.6485","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":"2026-05-18T04:01:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gtkFI+tTdBdS6HcOqsX9aYBvgr3NCKigU7xYY1WGYkk2ianb+l3IapUsgMtI2ipSywjikUXyYBYTWyw+1NHjBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T11:46:17.505128Z"},"content_sha256":"7a76a33e3bfd873541731874c79217daa0632ef25f494ee3bf4dc70965ada956","schema_version":"1.0","event_id":"sha256:7a76a33e3bfd873541731874c79217daa0632ef25f494ee3bf4dc70965ada956"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6IWD2J63SQEFHVNBBSIJ6XLHHP/bundle.json","state_url":"https://pith.science/pith/6IWD2J63SQEFHVNBBSIJ6XLHHP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6IWD2J63SQEFHVNBBSIJ6XLHHP/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":"2026-06-24T11:46:17Z","links":{"resolver":"https://pith.science/pith/6IWD2J63SQEFHVNBBSIJ6XLHHP","bundle":"https://pith.science/pith/6IWD2J63SQEFHVNBBSIJ6XLHHP/bundle.json","state":"https://pith.science/pith/6IWD2J63SQEFHVNBBSIJ6XLHHP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6IWD2J63SQEFHVNBBSIJ6XLHHP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:6IWD2J63SQEFHVNBBSIJ6XLHHP","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":"eeeafcf0163042426ad1254f3e1c7d8ea7f9fb9a379d85b00df26147c0fbb2f0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2012-02-29T08:50:09Z","title_canon_sha256":"7185edfed01e9eefa08279d363e5a9ae3d419690df4f46a622112c0d9edecc9f"},"schema_version":"1.0","source":{"id":"1202.6485","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1202.6485","created_at":"2026-05-18T04:01:12Z"},{"alias_kind":"arxiv_version","alias_value":"1202.6485v1","created_at":"2026-05-18T04:01:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1202.6485","created_at":"2026-05-18T04:01:12Z"},{"alias_kind":"pith_short_12","alias_value":"6IWD2J63SQEF","created_at":"2026-05-18T12:26:56Z"},{"alias_kind":"pith_short_16","alias_value":"6IWD2J63SQEFHVNB","created_at":"2026-05-18T12:26:56Z"},{"alias_kind":"pith_short_8","alias_value":"6IWD2J63","created_at":"2026-05-18T12:26:56Z"}],"graph_snapshots":[{"event_id":"sha256:7a76a33e3bfd873541731874c79217daa0632ef25f494ee3bf4dc70965ada956","target":"graph","created_at":"2026-05-18T04:01:12Z","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":"Standard multivariate analysis methods aim to identify and summarize the main structures in large data sets containing the description of a number of observations by several variables. In many cases, spatial information is also available for each observation, so that a map can be associated to the multivariate data set. Two main objectives are relevant in the analysis of spatial multivariate data: summarizing covariation structures and identifying spatial patterns. In practice, achieving both goals simultaneously is a statistical challenge, and a range of methods have been developed that offer","authors_text":"St\\'ephane Dray, Thibaut Jombart","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2012-02-29T08:50:09Z","title":"Revisiting Guerry's data: Introducing spatial constraints in multivariate analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1202.6485","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:b4eba01529ed353a7c56babb6acf02319b0964aa22866084d055f9d53a314bdb","target":"record","created_at":"2026-05-18T04:01:12Z","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":"eeeafcf0163042426ad1254f3e1c7d8ea7f9fb9a379d85b00df26147c0fbb2f0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2012-02-29T08:50:09Z","title_canon_sha256":"7185edfed01e9eefa08279d363e5a9ae3d419690df4f46a622112c0d9edecc9f"},"schema_version":"1.0","source":{"id":"1202.6485","kind":"arxiv","version":1}},"canonical_sha256":"f22c3d27db940853d5a10c909f5d673bf449985bde07dd571980d074ab341748","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f22c3d27db940853d5a10c909f5d673bf449985bde07dd571980d074ab341748","first_computed_at":"2026-05-18T04:01:12.414207Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T04:01:12.414207Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RQGY3rolLtn0E8NpFR6woMdMaBFR6RYynobLbSQKyFUINoSTKYzSAKy4S4UHJCXsQxi719rS7Mz6g9h9uVECDw==","signature_status":"signed_v1","signed_at":"2026-05-18T04:01:12.415103Z","signed_message":"canonical_sha256_bytes"},"source_id":"1202.6485","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b4eba01529ed353a7c56babb6acf02319b0964aa22866084d055f9d53a314bdb","sha256:7a76a33e3bfd873541731874c79217daa0632ef25f494ee3bf4dc70965ada956"],"state_sha256":"750b6682365d19b5aa592e64c4f0665a64502785d51cfe7cd6d33c78784e0b48"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zgjO3zCdranoqYL23YfQTRj4SAp6xMRPOBYpIRuTnwj1fRq9796v1YgtSkOOvdBQ6kHYT8KPWvCUdir2Li4DCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-24T11:46:17.507698Z","bundle_sha256":"65bffb75c82cae437f3464aa0ec98d2094e844c90074df9a1650a11a6f58e10b"}}