{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:ZBCI5NQ47GRHWYU27QLLFZOQ7J","short_pith_number":"pith:ZBCI5NQ4","canonical_record":{"source":{"id":"2607.03586","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"stat.ME","submitted_at":"2026-07-03T20:06:29Z","cross_cats_sorted":["stat.CO"],"title_canon_sha256":"5aced62527e4ba3c50ecfafcf05d734d8619ac93ff4f722d94801d1bf8b2f760","abstract_canon_sha256":"0655d0960138de74bf50927466a64ed3be246722e9be3c47abfe399adc0cc0d0"},"schema_version":"1.0"},"canonical_sha256":"c8448eb61cf9a27b629afc16b2e5d0fa5cf32b76e6c899e09d643799c52830fb","source":{"kind":"arxiv","id":"2607.03586","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.03586","created_at":"2026-07-07T02:17:56Z"},{"alias_kind":"arxiv_version","alias_value":"2607.03586v1","created_at":"2026-07-07T02:17:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.03586","created_at":"2026-07-07T02:17:56Z"},{"alias_kind":"pith_short_12","alias_value":"ZBCI5NQ47GRH","created_at":"2026-07-07T02:17:56Z"},{"alias_kind":"pith_short_16","alias_value":"ZBCI5NQ47GRHWYU2","created_at":"2026-07-07T02:17:56Z"},{"alias_kind":"pith_short_8","alias_value":"ZBCI5NQ4","created_at":"2026-07-07T02:17:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:ZBCI5NQ47GRHWYU27QLLFZOQ7J","target":"record","payload":{"canonical_record":{"source":{"id":"2607.03586","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"stat.ME","submitted_at":"2026-07-03T20:06:29Z","cross_cats_sorted":["stat.CO"],"title_canon_sha256":"5aced62527e4ba3c50ecfafcf05d734d8619ac93ff4f722d94801d1bf8b2f760","abstract_canon_sha256":"0655d0960138de74bf50927466a64ed3be246722e9be3c47abfe399adc0cc0d0"},"schema_version":"1.0"},"canonical_sha256":"c8448eb61cf9a27b629afc16b2e5d0fa5cf32b76e6c899e09d643799c52830fb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-07T02:17:56.005574Z","signature_b64":"/1AWJ6o8lT59RUUsWO+biRZ6oJ/p32T5/XuiM0MEuyAzmEkGaBLYQzbbykR4bvG/ttPfBb4COsQXFuLO8LZfDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c8448eb61cf9a27b629afc16b2e5d0fa5cf32b76e6c899e09d643799c52830fb","last_reissued_at":"2026-07-07T02:17:56.004869Z","signature_status":"signed_v1","first_computed_at":"2026-07-07T02:17:56.004869Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.03586","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":"2026-07-07T02:17:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RjEOZizkYXxfMH8g95gwD2d+kGMIJEVBQQ1HdhspcqPFasoLwPo4VsGzZquu3prlLrppvnieox/ApmP/f2gKCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T12:41:45.721649Z"},"content_sha256":"da4b42b60585171dfe87bbdb978a9585e77b0c310c55f5999e7e8fcb0e6da3d4","schema_version":"1.0","event_id":"sha256:da4b42b60585171dfe87bbdb978a9585e77b0c310c55f5999e7e8fcb0e6da3d4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:ZBCI5NQ47GRHWYU27QLLFZOQ7J","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayes Estimation of GLARMA Models With Applications","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["stat.CO"],"primary_cat":"stat.ME","authors_text":"Ana Julia Alves C\\^amara, Guilherme Pumi","submitted_at":"2026-07-03T20:06:29Z","abstract_excerpt":"This work presents a Bayesian approach for parameter estimation in the class of Generalized Linear Autoregressive Moving Average (GLARMA) models, extending the methodology beyond the common exponential family setting. The proposed framework accommodates positive, double-bounded, and count time series through a unified MCMC-based estimation procedure implemented in \\texttt{nimble}. We discuss prior specifications for the model parameters and conduct an extensive Monte Carlo simulation study to evaluate the finite-sample performance of the approach under three distinct data-generating mechanisms"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.03586","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/2607.03586/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":"2026-07-07T02:17:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gwT+XFJNS+n9PHqJTwOesMswr+ow8fbiLoSwiJDQ9ZWzQjJz6snpuGyx1rvP53I9Nf8kSRADinviF3q+OEOmAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T12:41:45.722194Z"},"content_sha256":"42729e80651b6ad2c85500d32857495a2ecf544924f247112149020ca8556fb2","schema_version":"1.0","event_id":"sha256:42729e80651b6ad2c85500d32857495a2ecf544924f247112149020ca8556fb2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZBCI5NQ47GRHWYU27QLLFZOQ7J/bundle.json","state_url":"https://pith.science/pith/ZBCI5NQ47GRHWYU27QLLFZOQ7J/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZBCI5NQ47GRHWYU27QLLFZOQ7J/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":"2026-08-10T12:41:45Z","links":{"resolver":"https://pith.science/pith/ZBCI5NQ47GRHWYU27QLLFZOQ7J","bundle":"https://pith.science/pith/ZBCI5NQ47GRHWYU27QLLFZOQ7J/bundle.json","state":"https://pith.science/pith/ZBCI5NQ47GRHWYU27QLLFZOQ7J/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZBCI5NQ47GRHWYU27QLLFZOQ7J/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:ZBCI5NQ47GRHWYU27QLLFZOQ7J","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":"0655d0960138de74bf50927466a64ed3be246722e9be3c47abfe399adc0cc0d0","cross_cats_sorted":["stat.CO"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"stat.ME","submitted_at":"2026-07-03T20:06:29Z","title_canon_sha256":"5aced62527e4ba3c50ecfafcf05d734d8619ac93ff4f722d94801d1bf8b2f760"},"schema_version":"1.0","source":{"id":"2607.03586","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.03586","created_at":"2026-07-07T02:17:56Z"},{"alias_kind":"arxiv_version","alias_value":"2607.03586v1","created_at":"2026-07-07T02:17:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.03586","created_at":"2026-07-07T02:17:56Z"},{"alias_kind":"pith_short_12","alias_value":"ZBCI5NQ47GRH","created_at":"2026-07-07T02:17:56Z"},{"alias_kind":"pith_short_16","alias_value":"ZBCI5NQ47GRHWYU2","created_at":"2026-07-07T02:17:56Z"},{"alias_kind":"pith_short_8","alias_value":"ZBCI5NQ4","created_at":"2026-07-07T02:17:56Z"}],"graph_snapshots":[{"event_id":"sha256:42729e80651b6ad2c85500d32857495a2ecf544924f247112149020ca8556fb2","target":"graph","created_at":"2026-07-07T02:17:56Z","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/2607.03586/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This work presents a Bayesian approach for parameter estimation in the class of Generalized Linear Autoregressive Moving Average (GLARMA) models, extending the methodology beyond the common exponential family setting. The proposed framework accommodates positive, double-bounded, and count time series through a unified MCMC-based estimation procedure implemented in \\texttt{nimble}. We discuss prior specifications for the model parameters and conduct an extensive Monte Carlo simulation study to evaluate the finite-sample performance of the approach under three distinct data-generating mechanisms","authors_text":"Ana Julia Alves C\\^amara, Guilherme Pumi","cross_cats":["stat.CO"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"stat.ME","submitted_at":"2026-07-03T20:06:29Z","title":"Bayes Estimation of GLARMA Models With Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.03586","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:da4b42b60585171dfe87bbdb978a9585e77b0c310c55f5999e7e8fcb0e6da3d4","target":"record","created_at":"2026-07-07T02:17:56Z","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":"0655d0960138de74bf50927466a64ed3be246722e9be3c47abfe399adc0cc0d0","cross_cats_sorted":["stat.CO"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"stat.ME","submitted_at":"2026-07-03T20:06:29Z","title_canon_sha256":"5aced62527e4ba3c50ecfafcf05d734d8619ac93ff4f722d94801d1bf8b2f760"},"schema_version":"1.0","source":{"id":"2607.03586","kind":"arxiv","version":1}},"canonical_sha256":"c8448eb61cf9a27b629afc16b2e5d0fa5cf32b76e6c899e09d643799c52830fb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c8448eb61cf9a27b629afc16b2e5d0fa5cf32b76e6c899e09d643799c52830fb","first_computed_at":"2026-07-07T02:17:56.004869Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-07T02:17:56.004869Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/1AWJ6o8lT59RUUsWO+biRZ6oJ/p32T5/XuiM0MEuyAzmEkGaBLYQzbbykR4bvG/ttPfBb4COsQXFuLO8LZfDw==","signature_status":"signed_v1","signed_at":"2026-07-07T02:17:56.005574Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.03586","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:da4b42b60585171dfe87bbdb978a9585e77b0c310c55f5999e7e8fcb0e6da3d4","sha256:42729e80651b6ad2c85500d32857495a2ecf544924f247112149020ca8556fb2"],"state_sha256":"fc56cbef67e3d7786810c14f729204a4ba98b8990c8c552ba211b80d0ccd5a88"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UBV0s0gTrAyKVKCrgIZd0qt1lSj/B306OiZ7GMgv1AXyAmIuTEjU5k7fCq4wZj66mWxXEeYE/g75kGmDju9BDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T12:41:45.726712Z","bundle_sha256":"701b35164263612dc9da22b49de3d9c7888cd3336371a11a8dace4ad8fdd6102"}}