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Error Estimate and Convergence Analysis of Moment-Preserving Discrete Approximations of Continuous Distributions
http://hdl.handle.net/10445/8041
http://hdl.handle.net/10445/8041a278d0a2-beaa-4cd2-b236-4f409a048d59
| Item type | 会議発表論文 / Conference Paper(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2015-03-26 | |||||
| タイトル | ||||||
| タイトル | Error Estimate and Convergence Analysis of Moment-Preserving Discrete Approximations of Continuous Distributions | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
| 資源タイプ | conference paper | |||||
| アクセス権 | ||||||
| アクセス権 | metadata only access | |||||
| アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
| 著者 |
田中, 健一郎
× 田中, 健一郎× Toda, Alexis Akira |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | We propose a numerical method to approximate a given continuous distribution by a discrete distribution with prescribed moments. The approximation is achieved by minimizing the Kullback-Leibler information of the unknown discrete distribution relative to the known continuous distribution (evaluated at given discrete points) subject to some moment constraints. We study the theoretical error bound and the convergence property of the method. The order of the theoretical error bound of the expectation of any bounded measurable function with respect to the approximating discrete distribution is never worse than the integration formula we start with, and therefore the approximating discrete distribution weakly converges to the given continuous distribution. Moreover, we present some numerical examples that show the advantage of our method. | |||||
| 書誌情報 |
AIP Conf. Proc. 巻 1636, 号 30, 発行日 2014 |
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| 査読有無 | ||||||
| 値 | あり/yes | |||||
| 研究業績種別 | ||||||
| 値 | 国際会議/International Conference | |||||
| 単著共著 | ||||||
| 値 | 共著/joint | |||||
| 出版者 | ||||||
| 出版者 | AIP Publishing | |||||
