Approximation Theorems of Mathematical Statistics
Approximation Theorems of Mathematical Statistics
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DOI：
10.1002/9780470316481
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发表时间：
1980
期刊：
影响因子：
--
通讯作者：
Ing Rj Ser
中科院分区：
文献类型：
--
作者：
Ing Rj Ser
近似定理的数理统计这方便的平装版使统计学的开创性文本访问新一代的学生和从业者。数理统计的近似定理涵盖了数理统计中有用的广泛的极限定理，沿着证明方法和应用技术。操纵”概率”定理获得”统计”定理强调。除了这些基本的统计定理的知识，这一主题的清晰介绍赋予了概率论的工具作用的赞赏。这本书使学生和实践专业人员在统计，一般数学，运筹学和工程的要点：* 工具和基础，基本的渐近理论统计 * 统计的渐近计算从一个样本，包括更基本的统计向量的转换，强调渐近分布理论和强收敛 * 重要的特殊类的统计，如最大似然估计和其他渐近有效的程序; W。Hoeffding的U统计量和R.冯·米塞斯的”可微统计函数”* 作为方程的解（“M-估计”）、顺序统计量的线性函数（“L-统计量”）和秩统计量（“R-统计量”）获得的统计量 * 影响曲线的使用 * 统计检验程序的渐近相对效率方法
Approximation Theorems of Mathematical Statistics This convenient paperback edition makes a seminal text in statistics accessible to a new generation of students and practitioners. Approximation Theorems of Mathematical Statistics covers a broad range of limit theorems useful in mathematical statistics, along with methods of proof and techniques of application. The manipulation of" probability" theorems to obtain" statistical" theorems is emphasized. Besides a knowledge of these basic statistical theorems, this lucid introduction to the subject imparts an appreciation of the instrumental role of probability theory. The book makes accessible to students and practicing professionals in statistics, general mathematics, operations research, and engineering the essentials of:* The tools and foundations that are basic to asymptotic theory in statistics* The asymptotics of statistics computed from a sample, including transformations of vectors of more basic statistics, with emphasis on asymptotic distribution theory and strong convergence* Important special classes of statistics, such as maximum likelihood estimates and other asymptotic efficient procedures; W. Hoeffding's U-statistics and R. von Mises's" differentiable statistical functions"* Statistics obtained as solutions of equations (" M-estimates"), linear functions of order statistics (" L-statistics"), and rank statistics (" R-statistics")* Use of influence curves* Approaches toward asymptotic relative efficiency of statistical test procedures