{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:NCYFW7QO2WIHPHBAU3BQJCGJR5","short_pith_number":"pith:NCYFW7QO","canonical_record":{"source":{"id":"2005.05464","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2020-05-11T22:07:35Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"ae075accfde61dd037d2c228d19b1c9d24fe95eef6aa77725944efc02f073d0c","abstract_canon_sha256":"10c0c251e4e8e681ac3cab794003cb031a1559cce971a6e97fb9326862b3d69b"},"schema_version":"1.0"},"canonical_sha256":"68b05b7e0ed590779c20a6c30488c98f5c55f30a89f8ccfdb400041ed36a9ba0","source":{"kind":"arxiv","id":"2005.05464","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.05464","created_at":"2026-07-05T01:02:20Z"},{"alias_kind":"arxiv_version","alias_value":"2005.05464v1","created_at":"2026-07-05T01:02:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.05464","created_at":"2026-07-05T01:02:20Z"},{"alias_kind":"pith_short_12","alias_value":"NCYFW7QO2WIH","created_at":"2026-07-05T01:02:20Z"},{"alias_kind":"pith_short_16","alias_value":"NCYFW7QO2WIHPHBA","created_at":"2026-07-05T01:02:20Z"},{"alias_kind":"pith_short_8","alias_value":"NCYFW7QO","created_at":"2026-07-05T01:02:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:NCYFW7QO2WIHPHBAU3BQJCGJR5","target":"record","payload":{"canonical_record":{"source":{"id":"2005.05464","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2020-05-11T22:07:35Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"ae075accfde61dd037d2c228d19b1c9d24fe95eef6aa77725944efc02f073d0c","abstract_canon_sha256":"10c0c251e4e8e681ac3cab794003cb031a1559cce971a6e97fb9326862b3d69b"},"schema_version":"1.0"},"canonical_sha256":"68b05b7e0ed590779c20a6c30488c98f5c55f30a89f8ccfdb400041ed36a9ba0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:02:20.804359Z","signature_b64":"ESqIuBh9tmbFRWQdq7IagNrXS/BUyCH9GzmbSYJ6EhNVdVkmcejthNGwT9hh7M54FHoXRgFybPpIyqfdc2L+DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"68b05b7e0ed590779c20a6c30488c98f5c55f30a89f8ccfdb400041ed36a9ba0","last_reissued_at":"2026-07-05T01:02:20.803825Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:02:20.803825Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2005.05464","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":"2026-07-05T01:02:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aHtQLWWmFfw7o6JAXmG70sHcdxWDN+EW+l+gt4716nCkRbIwDXd9xjM7tSCsSxc5zPROEsOacTL9MivJgDGvCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T12:06:44.208691Z"},"content_sha256":"b0f7a30b69b575e245ba465a9595e5b5f1ca6812de244763bf390b165088837c","schema_version":"1.0","event_id":"sha256:b0f7a30b69b575e245ba465a9595e5b5f1ca6812de244763bf390b165088837c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:NCYFW7QO2WIHPHBAU3BQJCGJR5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Non-Separable Spatio-temporal Models via Transformed Gaussian Markov Random Fields","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"Douglas R. M. Azevedo, Marcos O. Prates, Michael R. Willig","submitted_at":"2020-05-11T22:07:35Z","abstract_excerpt":"Models that capture the spatial and temporal dynamics are applicable in many science fields. Non-separable spatio-temporal models were introduced in the literature to capture these features. However, these models are generally complicated in construction and interpretation. We introduce a class of non-separable Transformed Gaussian Markov Random Fields (TGMRF) in which the dependence structure is flexible and facilitates simple interpretations concerning spatial, temporal and spatio-temporal parameters. Moreover, TGMRF models have the advantage of allowing specialists to define any desired mar"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.05464","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2005.05464/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T01:02:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"589+5J7QH2NwIylqmT41RXlkV0MAplHiP0Y0edS+btJyh0ktG/BwONQEDQq6mFwNv1pTeZHn1+E0o9yeX45fAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T12:06:44.209070Z"},"content_sha256":"5ebb6f65ed047e06084805ebfe0190731605e4df0f957278a3d88cfc4042b67c","schema_version":"1.0","event_id":"sha256:5ebb6f65ed047e06084805ebfe0190731605e4df0f957278a3d88cfc4042b67c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NCYFW7QO2WIHPHBAU3BQJCGJR5/bundle.json","state_url":"https://pith.science/pith/NCYFW7QO2WIHPHBAU3BQJCGJR5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NCYFW7QO2WIHPHBAU3BQJCGJR5/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":"2026-07-07T12:06:44Z","links":{"resolver":"https://pith.science/pith/NCYFW7QO2WIHPHBAU3BQJCGJR5","bundle":"https://pith.science/pith/NCYFW7QO2WIHPHBAU3BQJCGJR5/bundle.json","state":"https://pith.science/pith/NCYFW7QO2WIHPHBAU3BQJCGJR5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NCYFW7QO2WIHPHBAU3BQJCGJR5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:NCYFW7QO2WIHPHBAU3BQJCGJR5","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":"10c0c251e4e8e681ac3cab794003cb031a1559cce971a6e97fb9326862b3d69b","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2020-05-11T22:07:35Z","title_canon_sha256":"ae075accfde61dd037d2c228d19b1c9d24fe95eef6aa77725944efc02f073d0c"},"schema_version":"1.0","source":{"id":"2005.05464","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.05464","created_at":"2026-07-05T01:02:20Z"},{"alias_kind":"arxiv_version","alias_value":"2005.05464v1","created_at":"2026-07-05T01:02:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.05464","created_at":"2026-07-05T01:02:20Z"},{"alias_kind":"pith_short_12","alias_value":"NCYFW7QO2WIH","created_at":"2026-07-05T01:02:20Z"},{"alias_kind":"pith_short_16","alias_value":"NCYFW7QO2WIHPHBA","created_at":"2026-07-05T01:02:20Z"},{"alias_kind":"pith_short_8","alias_value":"NCYFW7QO","created_at":"2026-07-05T01:02:20Z"}],"graph_snapshots":[{"event_id":"sha256:5ebb6f65ed047e06084805ebfe0190731605e4df0f957278a3d88cfc4042b67c","target":"graph","created_at":"2026-07-05T01:02:20Z","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/2005.05464/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Models that capture the spatial and temporal dynamics are applicable in many science fields. Non-separable spatio-temporal models were introduced in the literature to capture these features. However, these models are generally complicated in construction and interpretation. We introduce a class of non-separable Transformed Gaussian Markov Random Fields (TGMRF) in which the dependence structure is flexible and facilitates simple interpretations concerning spatial, temporal and spatio-temporal parameters. Moreover, TGMRF models have the advantage of allowing specialists to define any desired mar","authors_text":"Douglas R. M. Azevedo, Marcos O. Prates, Michael R. Willig","cross_cats":["stat.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2020-05-11T22:07:35Z","title":"Non-Separable Spatio-temporal Models via Transformed Gaussian Markov Random Fields"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.05464","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:b0f7a30b69b575e245ba465a9595e5b5f1ca6812de244763bf390b165088837c","target":"record","created_at":"2026-07-05T01:02:20Z","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":"10c0c251e4e8e681ac3cab794003cb031a1559cce971a6e97fb9326862b3d69b","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2020-05-11T22:07:35Z","title_canon_sha256":"ae075accfde61dd037d2c228d19b1c9d24fe95eef6aa77725944efc02f073d0c"},"schema_version":"1.0","source":{"id":"2005.05464","kind":"arxiv","version":1}},"canonical_sha256":"68b05b7e0ed590779c20a6c30488c98f5c55f30a89f8ccfdb400041ed36a9ba0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"68b05b7e0ed590779c20a6c30488c98f5c55f30a89f8ccfdb400041ed36a9ba0","first_computed_at":"2026-07-05T01:02:20.803825Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:02:20.803825Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ESqIuBh9tmbFRWQdq7IagNrXS/BUyCH9GzmbSYJ6EhNVdVkmcejthNGwT9hh7M54FHoXRgFybPpIyqfdc2L+DA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:02:20.804359Z","signed_message":"canonical_sha256_bytes"},"source_id":"2005.05464","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b0f7a30b69b575e245ba465a9595e5b5f1ca6812de244763bf390b165088837c","sha256:5ebb6f65ed047e06084805ebfe0190731605e4df0f957278a3d88cfc4042b67c"],"state_sha256":"7f5f84fced921fba2417ff0c9fb05f7ca6a385ca08b40c7b7859a7d0c8104361"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iqyG/WGHtIHAHzHBUw+X2gSPyRWbQkvexCtQGyCDnS0RrLBeoEQB4UgiYYRQYYZZswbaQBVFBSyKKGlBalr4Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T12:06:44.211039Z","bundle_sha256":"a1d13a5067daeb5e519199ca508072544587b3f50b52e94171c82bc8481ba2ef"}}