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数理统计-第2版

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数理统计-第2版

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作 者:(美)邵著

出 版 社:世界图书

出版时间:2009-10-1

I S B N:9787510005343

  • 数理统计-第2版
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    44.90元
  • 数理统计-第2版
  • 送货上门
  • 价格
    44.90元
  • 数理统计-第2版
  • 送货上门
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  • 数理统计
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    《数理统计(第2版)(英文版)》由世界图书出版公司出版。

    内容简介

    简介   《数理统计(第2版)(英文版)》由世界图书出版公司出版。

    作者简介

    目录

    preface to the first edition
    preface to the second edition
    chapter 1. probability theory
     1.1 probability spaces and random elements
      1.1.1 a-fields and measures
      1.1.2 measurable functions and distributions
     1.2 integration and differentiation
      1.2.1 integration
      1.2.2 radon-nikodym derivative
     1.3 distributions and their characteristics
      1.3.1 distributions and probability densities
      1.3.2 moments and moment inequalities
      1.3.3 moment generating and characteristic functions
     1.4 conditional expectations
      1.4.1 conditional expectations
      1.4.2 independence
      1.4.3 conditional distributions
      1.4.4 markov chains and martingales
    1.5 asymptotic theory
      1.5.1 convergence modes and stochastic orders
      1.5.2 weak convergence
      1.5.3 convergence of transformations
      1.5.4 the law of large numbers
      1.5.5 the central limit theorem
      1.5.6 edgeworth and cornish-fisher expansions
     1.6 exercises
    chapter 2. fundamentals of statistics
     2.1 populations, samples, and models
      2.1.1 populations and samples
      2.1.2 parametric and nonparametric models
      2.1.3 exponential and location-scale families
     2.2 statistics, sufficiency, and completeness
      2.2.1 statistics and their distributions
      2.2.2 sufficiency and minimal sufficiency
      2.2.3 complete statistics
     2.3 statistical decision theory
      2.3.1 decision rules, loss functions, and risks
      2.3.2 admissibility and optimmity
     2.4 statistical inference
      2.4.1 point estimators
      2.4.2 hypothesis tests
      2.4.3 confidence sets
     2.5 asymptotic criteria and inference
      2.5.1 consistency
      2.5.2 asymptotic bias, variance, and mse
      2.5.3 asymptotic inference
     2.6 exercises
    chapter 3. unbiased estimation
    3.1 the umvue
      3.1.1 sufficient and complete statistics
      3.1.2 a necessary andsufficient condition
      3.1.3 information inequality
      3.1.4 asymptotic properties of umvue's
    3.2 u-statistics
      3.2.1 some examples
      3.2.2 variances of u-statistics
      3.2.3 the projection method
     ……
    chapter 4. estimation in parametric models
    chapter 5. estimation in nonparametric models
    chapter 6. hypothesis tests
    chapter 7. confidence sets
    references
    list of notation
    list of abbreviations
    index of definitions, main results, and examples
    author index
    subject index

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