翻訳と辞書 Words near each other ・ Kernan "Skip" Hand ・ Kernan Corner, New Jersey ・ Kernascléden ・ Kernavė ・ Kerne Bridge ・ Kerne Bridge railway station ・ Kernel ・ Kernel (algebra) ・ Kernel (category theory) ・ Kernel (digital media company) ・ Kernel (EP) ・ Kernel (image processing) ・ Kernel (linear algebra) ・ Kernel (operating system) ・ Kernel (set theory) ・ Kernel (statistics) ・ Kernel adaptive filter ・ Kernel debugger ・ Kernel density estimation ・ Kernel eigenvoice ・ Kernel embedding of distributions ・ Kernel Fisher discriminant analysis ・ Kernel function for solving integral equation of surface radiation exchanges ・ Kernel Independent Transport Layer ・ Kernel marker ・ Kernel method ・ Kernel methods for vector output ・ Kernel Normal Form ・ Kernel panic ・ Kernel patch Dictionary Lists mini英和辞書 mini和英辞書 Webster 1913 Latin-English FOLDOC Wikipedia English ウィキペディア

翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Kernel (statistics) ： ウィキペディア英語版 Kernel (statistics) The term kernel has several distinct meanings in statistics. ==In Bayesian statistics== In statistics, especially in Bayesian statistics, the kernel of a probability density function (pdf) or probability mass function (pmf) is the form of the pdf or pmf in which any factors that are not functions of any of the variables in the domain are omitted. Note that such factors may well be functions of the parameters of the pdf or pmf. These factors form part of the normalization factor of the probability distribution, and are unnecessary in many situations. For example, in pseudo-random number sampling, most sampling algorithms ignore the normalization factor. In addition, in Bayesian analysis of conjugate prior distributions, the normalization factors are generally ignored during the calculations, and only the kernel considered. At the end, the form of the kernel is examined, and if it matches a known distribution, the normalization factor can be reinstated. Otherwise, it may be unnecessary (for example, if the distribution only needs to be sampled from). For many distributions, the kernel can be written in closed form, but not the normalization constant. An example is the normal distribution. Its probability density function is :$p(x|\backslash mu,\backslash sigma^2)\; =\; \backslash frac\}$ and the associated kernel is :$p(x|\backslash mu,\backslash sigma^2)\; \backslash propto\; e^\}$ Note that the factor in front of the exponential has been omitted, even though it contains the parameter $\backslash sigma^2$ , because it is not a function of the domain variable $x$ . 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Kernel (statistics)」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.