{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:VSR5OP7TYGFKJOFPGTI7SQIX55","short_pith_number":"pith:VSR5OP7T","schema_version":"1.0","canonical_sha256":"aca3d73ff3c18aa4b8af34d1f94117ef4f9721992fcbad0067a08e7272bc3c40","source":{"kind":"arxiv","id":"1710.10626","version":1},"attestation_state":"computed","paper":{"title":"Detecting Multiple Random Changepoints in Bayesian Piecewise Growth Mixture Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Eric F Lock, Maitreyee Bose, Nidhi Kohli","submitted_at":"2017-10-29T15:11:00Z","abstract_excerpt":"Piecewise growth mixture models (PGMM) are a flexible and useful class of methods for analyzing segmented trends in individual growth trajectory over time, where the individuals come from a mixture of two or more latent classes. These models allow each segment of the overall developmental process within each class to have a different functional form; examples include two linear phases of growth, or a quadratic phase followed by a linear phase. The changepoint (knot) is the time of transition from one developmental phase (segment) to another. Inferring the location of the changepoint(s) is ofte"},"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":"1710.10626","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-10-29T15:11:00Z","cross_cats_sorted":[],"title_canon_sha256":"a25dfa4f31b0b3191849d336d8d1c10144c77db2dff41adddb9f93a2c3aa4ca0","abstract_canon_sha256":"cf5e5e0ce8d4f1fd340e7309d905ec6b79154f2a57da4f3cf3ef7bf2b60f5583"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:03:00.232305Z","signature_b64":"99ZGt/ju+YUDsdkeNKcfM4vO964ldvSXEottB5mYm79NVFQ36YeHm4TNi82SNgDCnX3RQw41GLRdbEzyHp0TCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aca3d73ff3c18aa4b8af34d1f94117ef4f9721992fcbad0067a08e7272bc3c40","last_reissued_at":"2026-05-18T00:03:00.231740Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:03:00.231740Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Detecting Multiple Random Changepoints in Bayesian Piecewise Growth Mixture Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Eric F Lock, Maitreyee Bose, Nidhi Kohli","submitted_at":"2017-10-29T15:11:00Z","abstract_excerpt":"Piecewise growth mixture models (PGMM) are a flexible and useful class of methods for analyzing segmented trends in individual growth trajectory over time, where the individuals come from a mixture of two or more latent classes. These models allow each segment of the overall developmental process within each class to have a different functional form; examples include two linear phases of growth, or a quadratic phase followed by a linear phase. The changepoint (knot) is the time of transition from one developmental phase (segment) to another. Inferring the location of the changepoint(s) is ofte"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.10626","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1710.10626","created_at":"2026-05-18T00:03:00.231833+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.10626v1","created_at":"2026-05-18T00:03:00.231833+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.10626","created_at":"2026-05-18T00:03:00.231833+00:00"},{"alias_kind":"pith_short_12","alias_value":"VSR5OP7TYGFK","created_at":"2026-05-18T12:31:49.984773+00:00"},{"alias_kind":"pith_short_16","alias_value":"VSR5OP7TYGFKJOFP","created_at":"2026-05-18T12:31:49.984773+00:00"},{"alias_kind":"pith_short_8","alias_value":"VSR5OP7T","created_at":"2026-05-18T12:31:49.984773+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/VSR5OP7TYGFKJOFPGTI7SQIX55","json":"https://pith.science/pith/VSR5OP7TYGFKJOFPGTI7SQIX55.json","graph_json":"https://pith.science/api/pith-number/VSR5OP7TYGFKJOFPGTI7SQIX55/graph.json","events_json":"https://pith.science/api/pith-number/VSR5OP7TYGFKJOFPGTI7SQIX55/events.json","paper":"https://pith.science/paper/VSR5OP7T"},"agent_actions":{"view_html":"https://pith.science/pith/VSR5OP7TYGFKJOFPGTI7SQIX55","download_json":"https://pith.science/pith/VSR5OP7TYGFKJOFPGTI7SQIX55.json","view_paper":"https://pith.science/paper/VSR5OP7T","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.10626&json=true","fetch_graph":"https://pith.science/api/pith-number/VSR5OP7TYGFKJOFPGTI7SQIX55/graph.json","fetch_events":"https://pith.science/api/pith-number/VSR5OP7TYGFKJOFPGTI7SQIX55/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VSR5OP7TYGFKJOFPGTI7SQIX55/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VSR5OP7TYGFKJOFPGTI7SQIX55/action/storage_attestation","attest_author":"https://pith.science/pith/VSR5OP7TYGFKJOFPGTI7SQIX55/action/author_attestation","sign_citation":"https://pith.science/pith/VSR5OP7TYGFKJOFPGTI7SQIX55/action/citation_signature","submit_replication":"https://pith.science/pith/VSR5OP7TYGFKJOFPGTI7SQIX55/action/replication_record"}},"created_at":"2026-05-18T00:03:00.231833+00:00","updated_at":"2026-05-18T00:03:00.231833+00:00"}