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確率密度関数の推定としての正規混合分布の解析とその周辺に関する研究
https://maebashi-it.repo.nii.ac.jp/records/14
https://maebashi-it.repo.nii.ac.jp/records/14ac2da179-b923-4b46-9367-c435bba98863
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
学位論文塚越.pdf (2.4 MB)
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| Item type | 学位論文 / Thesis or Dissertation_02(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2015-06-10 | |||||
| 和題 | ||||||
| タイトル | 確率密度関数の推定としての正規混合分布の解析とその周辺に関する研究 | |||||
| 言語 | ja | |||||
| 英題 | ||||||
| その他のタイトル | Research on the Gaussian Mixture distribution analysis as estimation of Probability Density Function and it's the periphery | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | jpn | |||||
| キーワード | ||||||
| 言語 | ja | |||||
| 主題Scheme | Other | |||||
| 主題 | 確率密度関数の推定 | |||||
| キーワード | ||||||
| 言語 | ja | |||||
| 主題Scheme | Other | |||||
| 主題 | 正規混合分布 | |||||
| キーワード | ||||||
| 言語 | ja | |||||
| 主題Scheme | Other | |||||
| 主題 | V.D spline関数 | |||||
| キーワード | ||||||
| 言語 | ja | |||||
| 主題Scheme | Other | |||||
| 主題 | ウェーブレット変換 | |||||
| キーワード | ||||||
| 言語 | ja | |||||
| 主題Scheme | Other | |||||
| 主題 | 耐性菌 | |||||
| キーワード | ||||||
| 言語 | ja | |||||
| 主題Scheme | Other | |||||
| 主題 | 花粉の飛散状況 | |||||
| キーワード | ||||||
| 言語 | ja | |||||
| 主題Scheme | Other | |||||
| 主題 | 品質工学 | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_db06 | |||||
| 資源タイプ | doctoral thesis | |||||
| アクセス権 | ||||||
| アクセス権 | open access | |||||
| アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||
| 著者 |
塚越, 清
× 塚越, 清 |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | In statistics, Mixture distribution model is a stochastic model for a measured data set to express existence of the subpopulation in a population, without requiring that the subpopulation to whom each observational data belongs should be identified. \nFormally, Mixture distribution model is equivalent to expressing the probability distributions of observational data in a population. \nHowever, it is although it is related to the problem relevant to Mixture distribution pulling out a population's characteristic out of subpopulation. \nMixture distribution model is used without subpopulation's identity information in order to make the statistical inference about the characteristic of the subpopulation who was able to give only the observational data about a population simultaneously. \nSome methods of fitting Mixture distribution model to observational data contain the step considered that subpopulation's assumed identity originates in each observational data (or gravity to such subpopulation). \nThis paper considered these matters from the similarity of the linear combination of an element function with the estimation problem of a Probability Density Function which used the Kernel function, and the estimation problem of the Probability Density Function using a Spline function. \nHow to take Translate in arrangement of knots of the estimation problem of the Probability Density Function using the method of Band width picking in the estimation problem of the Probability Density Function using a Kernel function and a Spline function and Wavelets analysis and Scale has a related thing.\nAt the end of this doctoral thesis, Application to an analysis of the problem of resistant bacteria and the scatter situation of the pollen and a problem of quality control is described. | |||||
| 学位名 | ||||||
| 学位名 | 博士(工学) | |||||
| 学位授与機関 | ||||||
| 学位授与機関識別子Scheme | kakenhi | |||||
| 学位授与機関識別子 | 22303 | |||||
| 学位授与機関名 | 前橋工科大学 | |||||
| 学位授与年月日 | ||||||
| 学位授与年月日 | 2015-03-25 | |||||
| 学位授与番号 | ||||||
| 学位授与番号 | 甲第15号 | |||||
| 更新日 | ||||||
| 値 | 2019-10-28 | |||||
