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Approximation of conditional moments of diffusion processes
http://hdl.handle.net/2241/00150101
http://hdl.handle.net/2241/001501013f7a311e-5dd6-4aaa-9ee4-14161ac1d910
名前 / ファイル | ライセンス | アクション |
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IJCNAA_1(2)_163 (276.8 kB)
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Item type | Journal Article(1) | |||||
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公開日 | 2018-01-12 | |||||
タイトル | ||||||
タイトル | Approximation of conditional moments of diffusion processes | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題 | Approximation | |||||
キーワード | ||||||
主題 | Conditional moments | |||||
キーワード | ||||||
主題 | Diffusion process | |||||
キーワード | ||||||
主題 | Ordinary differential equation | |||||
キーワード | ||||||
主題 | Stochastic differential equation | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
著者 |
SHOJI, Isao
× SHOJI, Isao |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | 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. | |||||
書誌情報 |
International Journal of Computational and Numerical Analysis and Applications 巻 1, 号 2, p. 163-190, 発行日 2002 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 0975-0452 | |||||
著者版フラグ | ||||||
値 | author | |||||
出版者 | ||||||
出版者 | Academic Publications Ltd. |