{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:6TVJTNL57WCD3GNXNRYW4EQYTU","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":"b2d266446e9af8d2182d9820c2151d09635356c36ae543082f75e690494c28b2","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-09-14T12:35:04Z","title_canon_sha256":"79d70a7ceda4d08966bd98099502603e82bd1418d7bc2de4b92d68d02fd0692c"},"schema_version":"1.0","source":{"id":"1609.04237","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1609.04237","created_at":"2026-05-18T01:04:38Z"},{"alias_kind":"arxiv_version","alias_value":"1609.04237v1","created_at":"2026-05-18T01:04:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.04237","created_at":"2026-05-18T01:04:38Z"},{"alias_kind":"pith_short_12","alias_value":"6TVJTNL57WCD","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_16","alias_value":"6TVJTNL57WCD3GNX","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_8","alias_value":"6TVJTNL5","created_at":"2026-05-18T12:30:04Z"}],"graph_snapshots":[{"event_id":"sha256:56d335fd82e2a974ec3fea4ccf2c19b28e9ed34fce699b05d27f08e3eff3e6c4","target":"graph","created_at":"2026-05-18T01:04:38Z","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":"In this paper, we study parametric nonlinear regression under the Harris recurrent Markov chain framework. We first consider the nonlinear least squares estimators of the parameters in the homoskedastic case, and establish asymptotic theory for the proposed estimators. Our results show that the convergence rates for the estimators rely not only on the properties of the nonlinear regression function, but also on the number of regenerations for the Harris recurrent Markov chain. Furthermore, we discuss the estimation of the parameter vector in a conditional volatility function, and apply our res","authors_text":"Dag Tj{\\o}stheim, Degui Li, Jiti Gao","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-09-14T12:35:04Z","title":"Estimation in nonlinear regression with Harris recurrent Markov chains"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.04237","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":"sha256:01ba818ebb888fab07b90b657a68811fb962c849d3b3fe15ce008fcd0c6a9722","target":"record","created_at":"2026-05-18T01:04:38Z","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":"b2d266446e9af8d2182d9820c2151d09635356c36ae543082f75e690494c28b2","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-09-14T12:35:04Z","title_canon_sha256":"79d70a7ceda4d08966bd98099502603e82bd1418d7bc2de4b92d68d02fd0692c"},"schema_version":"1.0","source":{"id":"1609.04237","kind":"arxiv","version":1}},"canonical_sha256":"f4ea99b57dfd843d99b76c716e12189d08ff673f255f6b19ca2dd4de9bd8a609","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f4ea99b57dfd843d99b76c716e12189d08ff673f255f6b19ca2dd4de9bd8a609","first_computed_at":"2026-05-18T01:04:38.518067Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:04:38.518067Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"guMCHYKD4Otk1zpw9Q0fS1291DaG9XPaSUv4c9S7f2GU7vwSW0ktYTyVq5xqxFxczq6RdktDMiDMQxojlT/nCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:04:38.518770Z","signed_message":"canonical_sha256_bytes"},"source_id":"1609.04237","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:01ba818ebb888fab07b90b657a68811fb962c849d3b3fe15ce008fcd0c6a9722","sha256:56d335fd82e2a974ec3fea4ccf2c19b28e9ed34fce699b05d27f08e3eff3e6c4"],"state_sha256":"72c2ac84fa55ae147eeb0f85b8432f339dd4b37d83954b03255086944ba74312"}