{"created":"2021-03-01T07:24:34.406070+00:00","id":44826,"links":{},"metadata":{"_buckets":{"deposit":"50f0e0bd-4aed-4ccd-be88-1a7ff71ebccf"},"_deposit":{"id":"44826","owners":[],"pid":{"revision_id":0,"type":"depid","value":"44826"},"status":"published"},"_oai":{"id":"oai:tsukuba.repo.nii.ac.jp:00044826","sets":["2871:2874:816","3:62:5591:6289"]},"item_5_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2002","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicPageEnd":"190","bibliographicPageStart":"163","bibliographicVolumeNumber":"1","bibliographic_titles":[{"bibliographic_title":"International Journal of Computational and Numerical Analysis and Applications"}]}]},"item_5_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"A computational method of conditional moments of d-dimensional diffusion processes is considered. We show that conditional moments of a diffusion process can be approximated by the solution to an ordinary differential equation whose coefficients are characterized by coefficients of the stochastic differential equation of the process. We also show that the method gives the exact conditional moments if a stochastic differential equation has a special form. The numerical experiment of estimating parameters of a nonlinear stochastic differential equation from discrete observation shows that the maximum likelihood estimation with the computed conditional moments performs better than a conventional discretization approach.","subitem_description_type":"Abstract"}]},"item_5_publisher_27":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Academic Publications Ltd."}]},"item_5_select_15":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_select_item":"author"}]},"item_5_source_id_7":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"0975-0452","subitem_source_identifier_type":"ISSN"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"SHOJI, Isao"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2018-01-12"}],"displaytype":"detail","filename":"IJCNAA_1(2)_163.pdf","filesize":[{"value":"276.8 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"IJCNAA_1(2)_163","url":"https://tsukuba.repo.nii.ac.jp/record/44826/files/IJCNAA_1(2)_163.pdf"},"version_id":"89660e4a-2d80-4fd9-a2b7-5e16f39b785b"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Approximation","subitem_subject_scheme":"Other"},{"subitem_subject":"Conditional moments","subitem_subject_scheme":"Other"},{"subitem_subject":"Diffusion process","subitem_subject_scheme":"Other"},{"subitem_subject":"Ordinary differential equation","subitem_subject_scheme":"Other"},{"subitem_subject":"Stochastic differential equation","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":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Approximation of conditional moments of diffusion processes","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Approximation of conditional moments of diffusion processes"}]},"item_type_id":"5","owner":"1","path":["816","6289"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-01-12"},"publish_date":"2018-01-12","publish_status":"0","recid":"44826","relation_version_is_last":true,"title":["Approximation of conditional moments of diffusion processes"],"weko_creator_id":"1","weko_shared_id":5},"updated":"2022-04-27T09:16:18.631303+00:00"}