{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:VY2MFTQKSHNZXF7UAOTZZ7COYE","short_pith_number":"pith:VY2MFTQK","canonical_record":{"source":{"id":"1511.00154","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2015-10-31T17:26:19Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"496271725b89cb993c0c1f2787edb84a7f5bb5dae2a254b2a0db0d5836e19ab0","abstract_canon_sha256":"fc5a13152f328445eef721b0dc32cec5314a740857a2815cb2cc0ba6a54122c5"},"schema_version":"1.0"},"canonical_sha256":"ae34c2ce0a91db9b97f403a79cfc4ec107e5444efcda80a469609b1d85c17021","source":{"kind":"arxiv","id":"1511.00154","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1511.00154","created_at":"2026-05-18T00:34:00Z"},{"alias_kind":"arxiv_version","alias_value":"1511.00154v2","created_at":"2026-05-18T00:34:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.00154","created_at":"2026-05-18T00:34:00Z"},{"alias_kind":"pith_short_12","alias_value":"VY2MFTQKSHNZ","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_16","alias_value":"VY2MFTQKSHNZXF7U","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_8","alias_value":"VY2MFTQK","created_at":"2026-05-18T12:29:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:VY2MFTQKSHNZXF7UAOTZZ7COYE","target":"record","payload":{"canonical_record":{"source":{"id":"1511.00154","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2015-10-31T17:26:19Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"496271725b89cb993c0c1f2787edb84a7f5bb5dae2a254b2a0db0d5836e19ab0","abstract_canon_sha256":"fc5a13152f328445eef721b0dc32cec5314a740857a2815cb2cc0ba6a54122c5"},"schema_version":"1.0"},"canonical_sha256":"ae34c2ce0a91db9b97f403a79cfc4ec107e5444efcda80a469609b1d85c17021","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:34:00.244648Z","signature_b64":"tK9u+z6nPeiMI4JiECAzTLIYB2TmvXS9b0sgCSOffurZQEOtCG8tkNd1DUznzeZEc6kfy6l741RwiT4piZHlDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ae34c2ce0a91db9b97f403a79cfc4ec107e5444efcda80a469609b1d85c17021","last_reissued_at":"2026-05-18T00:34:00.244015Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:34:00.244015Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1511.00154","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:34:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KG6UE9z/6vPiWsqGA2pzKWaKxxXtrMglU4zy0T0DWr3a2zB7WOD3PvoC3A1n8kVFEWrnB9R8L5zeg2u2FeAaCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T01:48:56.920835Z"},"content_sha256":"e2e0f71a957216f8c92ddbcc3f059ac5349dedfbddfe24107e2a62ee18e32c52","schema_version":"1.0","event_id":"sha256:e2e0f71a957216f8c92ddbcc3f059ac5349dedfbddfe24107e2a62ee18e32c52"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:VY2MFTQKSHNZXF7UAOTZZ7COYE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Bayesian Nonparametric approach to Reconstruction and Prediction of Random Dynamical Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"stat.AP","authors_text":"Christos Merkatas, Konstantinos Kaloudis, Spyridon J. Hatjispyros","submitted_at":"2015-10-31T17:26:19Z","abstract_excerpt":"We propose a Bayesian nonparametric mixture model for the reconstruction and prediction from observed time series data, of discretized stochastic dynamical systems, based on Markov Chain Monte Carlo methods (MCMC). Our results can be used by researchers in physical modeling interested in a fast and accurate estimation of low dimensional stochastic models when the size of the observed time series is small and the noise process (perhaps) is non-Gaussian. The inference procedure is demonstrated specifically in the case of polynomial maps of arbitrary degree and when a Geometric Stick Breaking mix"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.00154","kind":"arxiv","version":2},"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":"2026-05-18T00:34:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bWlRGYEd4S3pY1IV/yilUUlcmSiH8ip/rwZILNo037icWkxwP8MHdkTtAkoQwsju86TD4fXFELXRe62wjU5HBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T01:48:56.921164Z"},"content_sha256":"a8ebf919ab080db0fccc477e7895eb2a733c3167c12bcc7cd2930add1a02de0a","schema_version":"1.0","event_id":"sha256:a8ebf919ab080db0fccc477e7895eb2a733c3167c12bcc7cd2930add1a02de0a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VY2MFTQKSHNZXF7UAOTZZ7COYE/bundle.json","state_url":"https://pith.science/pith/VY2MFTQKSHNZXF7UAOTZZ7COYE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VY2MFTQKSHNZXF7UAOTZZ7COYE/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":"2026-06-25T01:48:56Z","links":{"resolver":"https://pith.science/pith/VY2MFTQKSHNZXF7UAOTZZ7COYE","bundle":"https://pith.science/pith/VY2MFTQKSHNZXF7UAOTZZ7COYE/bundle.json","state":"https://pith.science/pith/VY2MFTQKSHNZXF7UAOTZZ7COYE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VY2MFTQKSHNZXF7UAOTZZ7COYE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:VY2MFTQKSHNZXF7UAOTZZ7COYE","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":"fc5a13152f328445eef721b0dc32cec5314a740857a2815cb2cc0ba6a54122c5","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2015-10-31T17:26:19Z","title_canon_sha256":"496271725b89cb993c0c1f2787edb84a7f5bb5dae2a254b2a0db0d5836e19ab0"},"schema_version":"1.0","source":{"id":"1511.00154","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1511.00154","created_at":"2026-05-18T00:34:00Z"},{"alias_kind":"arxiv_version","alias_value":"1511.00154v2","created_at":"2026-05-18T00:34:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.00154","created_at":"2026-05-18T00:34:00Z"},{"alias_kind":"pith_short_12","alias_value":"VY2MFTQKSHNZ","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_16","alias_value":"VY2MFTQKSHNZXF7U","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_8","alias_value":"VY2MFTQK","created_at":"2026-05-18T12:29:47Z"}],"graph_snapshots":[{"event_id":"sha256:a8ebf919ab080db0fccc477e7895eb2a733c3167c12bcc7cd2930add1a02de0a","target":"graph","created_at":"2026-05-18T00:34:00Z","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 Bayesian nonparametric mixture model for the reconstruction and prediction from observed time series data, of discretized stochastic dynamical systems, based on Markov Chain Monte Carlo methods (MCMC). Our results can be used by researchers in physical modeling interested in a fast and accurate estimation of low dimensional stochastic models when the size of the observed time series is small and the noise process (perhaps) is non-Gaussian. The inference procedure is demonstrated specifically in the case of polynomial maps of arbitrary degree and when a Geometric Stick Breaking mix","authors_text":"Christos Merkatas, Konstantinos Kaloudis, Spyridon J. Hatjispyros","cross_cats":["stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2015-10-31T17:26:19Z","title":"A Bayesian Nonparametric approach to Reconstruction and Prediction of Random Dynamical Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.00154","kind":"arxiv","version":2},"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:e2e0f71a957216f8c92ddbcc3f059ac5349dedfbddfe24107e2a62ee18e32c52","target":"record","created_at":"2026-05-18T00:34:00Z","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":"fc5a13152f328445eef721b0dc32cec5314a740857a2815cb2cc0ba6a54122c5","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2015-10-31T17:26:19Z","title_canon_sha256":"496271725b89cb993c0c1f2787edb84a7f5bb5dae2a254b2a0db0d5836e19ab0"},"schema_version":"1.0","source":{"id":"1511.00154","kind":"arxiv","version":2}},"canonical_sha256":"ae34c2ce0a91db9b97f403a79cfc4ec107e5444efcda80a469609b1d85c17021","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ae34c2ce0a91db9b97f403a79cfc4ec107e5444efcda80a469609b1d85c17021","first_computed_at":"2026-05-18T00:34:00.244015Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:34:00.244015Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tK9u+z6nPeiMI4JiECAzTLIYB2TmvXS9b0sgCSOffurZQEOtCG8tkNd1DUznzeZEc6kfy6l741RwiT4piZHlDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:34:00.244648Z","signed_message":"canonical_sha256_bytes"},"source_id":"1511.00154","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e2e0f71a957216f8c92ddbcc3f059ac5349dedfbddfe24107e2a62ee18e32c52","sha256:a8ebf919ab080db0fccc477e7895eb2a733c3167c12bcc7cd2930add1a02de0a"],"state_sha256":"8b80cf133c049e56dfa44ec25ac5c0dd150ff70c7068c57004a8cb648f010b80"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cztcIwYOUsoTZ/vpm1opbOxmKBLdv4aZWEaqI3oT+lx73RAr6Eun4Zsa4fCcDvhlpgLNlESmxjjF7WKF+Vm/DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-25T01:48:56.923030Z","bundle_sha256":"801873aa5ba440bb559b362396ec20d92b399e3bd22e3d3dbcd5c0f739b8a0ca"}}