{"created":"2023-06-20T13:20:44.356514+00:00","id":774,"links":{},"metadata":{"_buckets":{"deposit":"e0042d54-6cf6-4fa1-b841-7b83c9ff0d66"},"_deposit":{"created_by":1,"id":"774","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"774"},"status":"published"},"_oai":{"id":"oai:ir.soken.ac.jp:00000774","sets":["2:429:17"]},"author_link":["0","0","0"],"item_1_creator_2":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"王, 健歡"}],"nameIdentifiers":[{"nameIdentifier":"0","nameIdentifierScheme":"WEKO"}]}]},"item_1_creator_3":{"attribute_name":"フリガナ","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"オウ, ケンカン"}],"nameIdentifiers":[{"nameIdentifier":"0","nameIdentifierScheme":"WEKO"}]}]},"item_1_date_granted_11":{"attribute_name":"学位授与年月日","attribute_value_mlt":[{"subitem_dategranted":"2006-03-24"}]},"item_1_degree_grantor_5":{"attribute_name":"学位授与機関","attribute_value_mlt":[{"subitem_degreegrantor":[{"subitem_degreegrantor_name":"総合研究大学院大学"}]}]},"item_1_degree_name_6":{"attribute_name":"学位名","attribute_value_mlt":[{"subitem_degreename":"博士（学術）"}]},"item_1_description_12":{"attribute_name":"要旨","attribute_value_mlt":[{"subitem_description":"This thesis summarizes statistical analysis of some multivariate heteroscedastic<br /> time series data, including 2 sets of data from physiological experiments and<br /> 2 sets of EEG data about anaesthesia and coma.<br />　　The aim of this thesis is to provide a statistical tool for analyzing multi-<br />variate data which contains non-stationary and heteroscedastic characteristics.<br />　　The main contribution of this thesis is that we combine the linear state<br /> space model and GARCH model to develop a state space-GARCH model.<br />The state space-GARCH model can describe the non-stationary characteristics<br /> of the system noise variance. In particular we adopt a special structure of<br /> the linear state space model to decompose a data into components by their<br /> frequencies. Combining a heteroscedasticity model and a state space model<br /> is carried out by fully utilizing the information of innovations and expected<br /> values from the filtering process.<br />　　Another contribution of the thesis is that we extend Akaike's NCR from<br /> constant noise variance to heterogeneous noise variance in order to study time-<br />varying causality. By applying heteroscedasticity models, the phenomenon of<br /> an evolving causality relationship can be depicted.<br />　　All these methods are illustrated by their application to EEG data including<br /> the study of consciousness under anaesthesia and coma, and also to a physical<br /> data of head and finger movement.","subitem_description_type":"Other"}]},"item_1_description_7":{"attribute_name":"学位記番号","attribute_value_mlt":[{"subitem_description":"総研大甲第948号","subitem_description_type":"Other"}]},"item_1_select_14":{"attribute_name":"所蔵","attribute_value_mlt":[{"subitem_select_item":"有"}]},"item_1_select_8":{"attribute_name":"研究科","attribute_value_mlt":[{"subitem_select_item":"複合科学研究科"}]},"item_1_select_9":{"attribute_name":"専攻","attribute_value_mlt":[{"subitem_select_item":"15 統計科学専攻"}]},"item_1_text_10":{"attribute_name":"学位授与年度","attribute_value_mlt":[{"subitem_text_value":"2005"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"WONG, Kin Foon Kevin","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"0","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2016-02-17"}],"displaytype":"simple","filename":"甲948_要旨.pdf","filesize":[{"value":"158.8 kB"}],"format":"application/pdf","licensetype":"license_11","mimetype":"application/pdf","url":{"label":"要旨・審査要旨","url":"https://ir.soken.ac.jp/record/774/files/甲948_要旨.pdf"},"version_id":"e5857e18-df88-492b-ba39-0226164bdfce"},{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2016-02-17"}],"displaytype":"simple","filename":"甲948_本文.pdf","filesize":[{"value":"7.9 MB"}],"format":"application/pdf","licensetype":"license_11","mimetype":"application/pdf","url":{"label":"本文","url":"https://ir.soken.ac.jp/record/774/files/甲948_本文.pdf"},"version_id":"434635c3-56c2-4711-8fad-c0015872352f"}]},"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":"thesis","resourceuri":"http://purl.org/coar/resource_type/c_46ec"}]},"item_title":"Multivariate Times Series Analysis of Heteroscedastic Date, with Application to Neuroscience","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Multivariate Times Series Analysis of Heteroscedastic Date, with Application to Neuroscience"},{"subitem_title":"Multivariate Times Series Analysis of Heteroscedastic Date, with Application to Neuroscience","subitem_title_language":"en"}]},"item_type_id":"1","owner":"1","path":["17"],"pubdate":{"attribute_name":"公開日","attribute_value":"2010-02-22"},"publish_date":"2010-02-22","publish_status":"0","recid":"774","relation_version_is_last":true,"title":["Multivariate Times Series Analysis of Heteroscedastic Date, with Application to Neuroscience"],"weko_creator_id":"1","weko_shared_id":1},"updated":"2023-06-20T15:59:49.176463+00:00"}