{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:PFPN6ZJRKNLVTEPZEXII5XUIJ4","short_pith_number":"pith:PFPN6ZJR","schema_version":"1.0","canonical_sha256":"795edf653153575991f925d08ede884f39970c21cb9661672bcf5d180e65f2e9","source":{"kind":"arxiv","id":"1108.3105","version":2},"attestation_state":"computed","paper":{"title":"Iterated Function System Models in Data Analysis: Detection and Separation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["nlin.CD"],"primary_cat":"math.DS","authors_text":"Elizabeth Bradley, James D. Meiss, Joshua Garland, Zachary Alexander","submitted_at":"2011-08-15T21:43:14Z","abstract_excerpt":"We investigate the use of iterated function system (IFS) models for data analysis. An IFS is a discrete dynamical system in which each time step corresponds to the application of one of a finite collection of maps. The maps, which represent distinct dynamical regimes, may act in some pre-determined sequence or may be applied in random order. An algorithm is developed to detect the sequence of regime switches under the assumption of continuity. This method is tested on a simple IFS and applied to an experimental computer performance data set. This methodology has a wide range of potential uses:"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1108.3105","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.DS","submitted_at":"2011-08-15T21:43:14Z","cross_cats_sorted":["nlin.CD"],"title_canon_sha256":"4ee78bec18e51964877274d0a65631b25a6a1d657c7e46bd98042e10769205e9","abstract_canon_sha256":"ba4a2b7b0f9f22f0aaf60d0af47b6f0691d854c85e1466e80c5b5496c1ba3b89"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:26:53.061640Z","signature_b64":"FJfFxGjN15FJSINuNZdMjNU/Z+mM/dRx1VfPCscVZ6gKLDdDdo2kIceCch6oi6FgRQyoL7hAGRcFjaGTUzDHAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"795edf653153575991f925d08ede884f39970c21cb9661672bcf5d180e65f2e9","last_reissued_at":"2026-05-18T03:26:53.061052Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:26:53.061052Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Iterated Function System Models in Data Analysis: Detection and Separation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["nlin.CD"],"primary_cat":"math.DS","authors_text":"Elizabeth Bradley, James D. Meiss, Joshua Garland, Zachary Alexander","submitted_at":"2011-08-15T21:43:14Z","abstract_excerpt":"We investigate the use of iterated function system (IFS) models for data analysis. An IFS is a discrete dynamical system in which each time step corresponds to the application of one of a finite collection of maps. The maps, which represent distinct dynamical regimes, may act in some pre-determined sequence or may be applied in random order. An algorithm is developed to detect the sequence of regime switches under the assumption of continuity. This method is tested on a simple IFS and applied to an experimental computer performance data set. This methodology has a wide range of potential uses:"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1108.3105","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1108.3105","created_at":"2026-05-18T03:26:53.061153+00:00"},{"alias_kind":"arxiv_version","alias_value":"1108.3105v2","created_at":"2026-05-18T03:26:53.061153+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1108.3105","created_at":"2026-05-18T03:26:53.061153+00:00"},{"alias_kind":"pith_short_12","alias_value":"PFPN6ZJRKNLV","created_at":"2026-05-18T12:26:39.201973+00:00"},{"alias_kind":"pith_short_16","alias_value":"PFPN6ZJRKNLVTEPZ","created_at":"2026-05-18T12:26:39.201973+00:00"},{"alias_kind":"pith_short_8","alias_value":"PFPN6ZJR","created_at":"2026-05-18T12:26:39.201973+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/PFPN6ZJRKNLVTEPZEXII5XUIJ4","json":"https://pith.science/pith/PFPN6ZJRKNLVTEPZEXII5XUIJ4.json","graph_json":"https://pith.science/api/pith-number/PFPN6ZJRKNLVTEPZEXII5XUIJ4/graph.json","events_json":"https://pith.science/api/pith-number/PFPN6ZJRKNLVTEPZEXII5XUIJ4/events.json","paper":"https://pith.science/paper/PFPN6ZJR"},"agent_actions":{"view_html":"https://pith.science/pith/PFPN6ZJRKNLVTEPZEXII5XUIJ4","download_json":"https://pith.science/pith/PFPN6ZJRKNLVTEPZEXII5XUIJ4.json","view_paper":"https://pith.science/paper/PFPN6ZJR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1108.3105&json=true","fetch_graph":"https://pith.science/api/pith-number/PFPN6ZJRKNLVTEPZEXII5XUIJ4/graph.json","fetch_events":"https://pith.science/api/pith-number/PFPN6ZJRKNLVTEPZEXII5XUIJ4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PFPN6ZJRKNLVTEPZEXII5XUIJ4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PFPN6ZJRKNLVTEPZEXII5XUIJ4/action/storage_attestation","attest_author":"https://pith.science/pith/PFPN6ZJRKNLVTEPZEXII5XUIJ4/action/author_attestation","sign_citation":"https://pith.science/pith/PFPN6ZJRKNLVTEPZEXII5XUIJ4/action/citation_signature","submit_replication":"https://pith.science/pith/PFPN6ZJRKNLVTEPZEXII5XUIJ4/action/replication_record"}},"created_at":"2026-05-18T03:26:53.061153+00:00","updated_at":"2026-05-18T03:26:53.061153+00:00"}