{"created":"2021-03-01T07:02:44.230240+00:00","id":42800,"links":{},"metadata":{"_buckets":{"deposit":"e85ae51c-9d1f-43c4-bca6-8df2a6f90aed"},"_deposit":{"id":"42800","owners":[],"pid":{"revision_id":0,"type":"depid","value":"42800"},"status":"published"},"_oai":{"id":"oai:repository.dl.itc.u-tokyo.ac.jp:00042800","sets":["62:7433:7434","9:7435:7436"]},"item_8_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2007-08","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"CIRJE-F-508","bibliographic_titles":[{"bibliographic_title":"Discussion paper series. CIRJE-F"}]}]},"item_8_description_13":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_8_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"This article introduces a new efficient simulation smoother and disturbance smoother for general state-space models where there exists a correlation between error terms of the measurement and state equations. The state vector is divided into several blocks where each block consists of many state variables. For each block, corresponding disturbances are sampled simultaneously from their conditional posterior distribution. The algorithm is based on the multivariate normal approximation of the conditional posterior density and exploits a conventional simulation smoother for a linear and Gaussian state space model. The performance of our method is illustrated using two examples (1) stochastic volatility models with leverage effects and (2) stochastic volatility models with leverage effects and state-dependent variances. The popular single move sampler which samples a state variable at a time is also conducted for comparison in the first example. It is shown that our proposed sampler produces considerable improvement in the mixing property of the Markov chain Monte Carlo chain.","subitem_description_type":"Abstract"}]},"item_8_description_6":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"Revised Version of 2003-F-221.","subitem_description_type":"Other"},{"subitem_description":"本文フィルはリンク先を参照のこと","subitem_description_type":"Other"}]},"item_8_publisher_20":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"日本経済国際共同センター"}]},"item_8_relation_25":{"attribute_name":"関係URI","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"http://www.cirje.e.u-tokyo.ac.jp/research/dp/2007/2007cf508ab.html","subitem_relation_type_select":"URI"}}]},"item_8_source_id_10":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11450569","subitem_source_identifier_type":"NCID"}]},"item_8_subject_15":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"330","subitem_subject_scheme":"NDC"}]},"item_8_text_21":{"attribute_name":"出版者別名","attribute_value_mlt":[{"subitem_text_value":"Center for International Research on the Japanese Economy"}]},"item_8_text_4":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Faculty of Economics, University of Tokyo"},{"subitem_text_value":"Institute of Economic Research, Hitotsubashi University"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Omori, Yasuhiro"}],"nameIdentifiers":[{"nameIdentifier":"98413","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Watanabe, Toshiaki"}],"nameIdentifiers":[{"nameIdentifier":"98414","nameIdentifierScheme":"WEKO"}]}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Bayesian analysis","subitem_subject_scheme":"Other"},{"subitem_subject":"Disturbance smoother","subitem_subject_scheme":"Other"},{"subitem_subject":"Kalman filter","subitem_subject_scheme":"Other"},{"subitem_subject":"Leverage　effects","subitem_subject_scheme":"Other"},{"subitem_subject":"Markov chain Monte Carlo","subitem_subject_scheme":"Other"},{"subitem_subject":"Metropolis-Hastings algorithm","subitem_subject_scheme":"Other"},{"subitem_subject":"Simulation　smoother","subitem_subject_scheme":"Other"},{"subitem_subject":"State space model","subitem_subject_scheme":"Other"},{"subitem_subject":"Stochastic volatility.","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"technical report","resourceuri":"http://purl.org/coar/resource_type/c_18gh"}]},"item_title":"Block sampler and posterior mode estimation for a nonlinear and non-Gaussian state-space model with correlated errors","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Block sampler and posterior mode estimation for a nonlinear and non-Gaussian state-space model with correlated errors"}]},"item_type_id":"8","owner":"1","path":["7436","7434"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-01-17"},"publish_date":"2017-01-17","publish_status":"0","recid":"42800","relation_version_is_last":true,"title":["Block sampler and posterior mode estimation for a nonlinear and non-Gaussian state-space model with correlated errors"],"weko_creator_id":"1","weko_shared_id":null},"updated":"2022-12-19T04:17:59.042691+00:00"}