《极值正则变差和点过程》讲述了学习独立同分布随机变量和向量的极值现象的数学背景和随机过程技巧。重在强调极值的三个重要的话题，规则变化函数的解析理论，点过程和随机测度的概率论，度量空间概率测度的若收敛的渐进分布逼近之间的联系。本书由雷斯尼克著。
| 书名 | 极值正则变差和点过程 |
| 分类 | 科学技术-自然科学-数学 |
| 作者 | (美)雷斯尼克 |
| 出版社 | 世界图书出版公司 |
| 下载 | 抱歉，不提供下载，请购买正版图书。 |
| 简介 | 编辑推荐 《极值正则变差和点过程》讲述了学习独立同分布随机变量和向量的极值现象的数学背景和随机过程技巧。重在强调极值的三个重要的话题，规则变化函数的解析理论，点过程和随机测度的概率论，度量空间概率测度的若收敛的渐进分布逼近之间的联系。本书由雷斯尼克著。 目录 Preface Preliminaries Uniform Convergence Inverses of Monotone Functions Convergence to Types Theorem and Limit Distributions of Maxima Regularly Varying Functions of a Real Variable Basics Deeper Results；Karamata’S Theorem Extensions of Regular Variation：兀．Variation．F．Variation Domains ofAttraction and Norming Constants Domain ofAttraction ofA（x）=exp Domain ofAttraction Domain ofAttraction Von Mises Conditions Equivalence Classes and Computation of Normalizing Constants Quality ofConvergence Moment Convergence Density Convergence Large Deviations． Uniform Rates of Convergence to Extreme Value Laws Uniform Rates of Convergence Uniform Rates of Convergence Point Processes Fundamentals Laplace Functionals Poisson Processes Definition and Construction Transformations of Poisson Processes Vague Convergence Weak Convergence of Point Processes and Random Measures Records and Extrema Processes Structure of Records Limit Laws for Records Extremal Processes Weak Convergence to Extremal Processes Skorohod Spaces Weak Convergence of Maximal Processes to Extremal Processes via Weak Convergence of Induced Point Processes Extreme Value Theory for Moving Averages Independence of k-Record Processes Multivariate Extremes Max．Infinite Divisibility An Example：The Bivariate Normal Characterizing Max．id Distributions Limit Distributions for Multivariate Extremes Characterizing Max．Stable Distributions Domains of Attraction；Multivariate Regular Variation Independence and Dependence Association Refe Inde |
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