{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:XHOR5EBPRLYB6XTLMWU4L47AWT","short_pith_number":"pith:XHOR5EBP","schema_version":"1.0","canonical_sha256":"b9dd1e902f8af01f5e6b65a9c5f3e0b4e3b54e81ad3e9023469c46b2a66e435c","source":{"kind":"arxiv","id":"1803.01699","version":2},"attestation_state":"computed","paper":{"title":"Banded Spatio-Temporal Autoregressions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Hansheng Wang, Qiwei Yao, Yingying Ma, Zhaoxing Gao","submitted_at":"2018-03-05T14:58:44Z","abstract_excerpt":"We propose a new class of spatio-temporal models with unknown and banded autoregressive coefficient matrices. The setting represents a sparse structure for high-dimensional spatial panel dynamic models when panel members represent economic (or other type) individuals at many different locations. The structure is practically meaningful when the order of panel members is arranged appropriately. Note that the implied autocovariance matrices are unlikely to be banded, and therefore, the proposal is radically different from the existing literature on the inference for high-dimensional banded covari"},"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":"1803.01699","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-03-05T14:58:44Z","cross_cats_sorted":[],"title_canon_sha256":"6841c00a89412d08db7615ebd61dcdccfd3a0fc03f18b827072c128f2a4cb5da","abstract_canon_sha256":"84fa755f6cf795d10c5b8828ddf61664abfcc71502e03f1cf99f8480b6ec97a6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:18:09.048432Z","signature_b64":"U0RBfJpwiQHrC3ex5zKq3/2F8JdXRgnrOgx2azMiSz5b+KmOeF2EUlI7wbPngiMmRZ8aS9zHW+7IIMz9mrniAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b9dd1e902f8af01f5e6b65a9c5f3e0b4e3b54e81ad3e9023469c46b2a66e435c","last_reissued_at":"2026-05-18T00:18:09.047920Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:18:09.047920Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Banded Spatio-Temporal Autoregressions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Hansheng Wang, Qiwei Yao, Yingying Ma, Zhaoxing Gao","submitted_at":"2018-03-05T14:58:44Z","abstract_excerpt":"We propose a new class of spatio-temporal models with unknown and banded autoregressive coefficient matrices. The setting represents a sparse structure for high-dimensional spatial panel dynamic models when panel members represent economic (or other type) individuals at many different locations. The structure is practically meaningful when the order of panel members is arranged appropriately. Note that the implied autocovariance matrices are unlikely to be banded, and therefore, the proposal is radically different from the existing literature on the inference for high-dimensional banded covari"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.01699","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":"1803.01699","created_at":"2026-05-18T00:18:09.047997+00:00"},{"alias_kind":"arxiv_version","alias_value":"1803.01699v2","created_at":"2026-05-18T00:18:09.047997+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.01699","created_at":"2026-05-18T00:18:09.047997+00:00"},{"alias_kind":"pith_short_12","alias_value":"XHOR5EBPRLYB","created_at":"2026-05-18T12:33:01.666342+00:00"},{"alias_kind":"pith_short_16","alias_value":"XHOR5EBPRLYB6XTL","created_at":"2026-05-18T12:33:01.666342+00:00"},{"alias_kind":"pith_short_8","alias_value":"XHOR5EBP","created_at":"2026-05-18T12:33:01.666342+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/XHOR5EBPRLYB6XTLMWU4L47AWT","json":"https://pith.science/pith/XHOR5EBPRLYB6XTLMWU4L47AWT.json","graph_json":"https://pith.science/api/pith-number/XHOR5EBPRLYB6XTLMWU4L47AWT/graph.json","events_json":"https://pith.science/api/pith-number/XHOR5EBPRLYB6XTLMWU4L47AWT/events.json","paper":"https://pith.science/paper/XHOR5EBP"},"agent_actions":{"view_html":"https://pith.science/pith/XHOR5EBPRLYB6XTLMWU4L47AWT","download_json":"https://pith.science/pith/XHOR5EBPRLYB6XTLMWU4L47AWT.json","view_paper":"https://pith.science/paper/XHOR5EBP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1803.01699&json=true","fetch_graph":"https://pith.science/api/pith-number/XHOR5EBPRLYB6XTLMWU4L47AWT/graph.json","fetch_events":"https://pith.science/api/pith-number/XHOR5EBPRLYB6XTLMWU4L47AWT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XHOR5EBPRLYB6XTLMWU4L47AWT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XHOR5EBPRLYB6XTLMWU4L47AWT/action/storage_attestation","attest_author":"https://pith.science/pith/XHOR5EBPRLYB6XTLMWU4L47AWT/action/author_attestation","sign_citation":"https://pith.science/pith/XHOR5EBPRLYB6XTLMWU4L47AWT/action/citation_signature","submit_replication":"https://pith.science/pith/XHOR5EBPRLYB6XTLMWU4L47AWT/action/replication_record"}},"created_at":"2026-05-18T00:18:09.047997+00:00","updated_at":"2026-05-18T00:18:09.047997+00:00"}