Sequential Methods and Their Applications
Sequential Methods and Their Applications
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序贯方法及其应用
DOI：
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
B. Silva
中科院分区：
文献类型：
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作者：
N. Mukhopadhyay;B. Silva
前言目标，覆盖范围和希望介绍回到原点最近的好转和积极的感觉目标覆盖范围的目的和范围最后的想法为什么顺序？介绍假设检验估计问题选择和排序问题计算机程序序贯概率比检验介绍终止和确定A和B函数和OC函数示例和实现辅助结果复合假设的序贯检验介绍方差检验均值检验相关系数检验Gamma形状参数双样本问题：序贯非参数检验简介均值检验：已知方差均值检验：正态总体均值的未知方差A-百分位数检验A-符号检验数据分析与结论宽度置信区间有界风险点估计最小风险点估计一些选定的推导位置估计：负指数分布简介固定-宽度置信区间最小风险点估计选择导数指数总体均值的点估计引言最小风险估计有界风险估计数据分析和结论其他选定的多阶段程序一些选定的衍生物MLE的固定宽度区间介绍一般序贯方法一般加速序贯方法示例数据分析和结论一些选定的衍生物估计中的无分布方法介绍固定宽度区间中位数数据分析的平均最小风险点估计值的宽度置信区间和平均有界长度置信区间，以及结论其他选定的多阶段程序一些选定的衍生物多元正态均值向量估计介绍固定大小置信区域：SIGMA = sigma 2 H固定大小置信区域：未知分散矩阵最小风险点估计：未知离差矩阵数据的分析和结论其他选定的多阶段程序一些选定的导数线性模型中的估计大小置信域最小风险点估计数据分析和结论其他选定的多阶段程序一些选定的衍生物估计两个正态均值的差异介绍固定-宽度置信区间最小风险点估计其他选定的多阶段程序一些选定的导数选择最佳正态总体介绍无差异区公式两阶段程序序贯程序数据分析和结论其他选定的多阶段程序一些选定的推导序贯贝叶斯估计介绍选定的固定样本量概念基本序贯概念数据分析选定的应用介绍临床试验综合害虫管理实验心理学：距离的认知园艺的问题其他当代应用领域附录：精选评论，表格和其他项目介绍大O（.）小O（）一些概率概念和结果非线性更新理论一瞥缩略语和记法统计表参考文献索引练习出现在每章的末尾。
Preface Objectives, Coverage, and Hopes Introduction Back to the Origin Recent Upturn and Positive Feelings The Objectives The Coverage Aims and Scope Final Thoughts Why Sequential? Introduction Tests of Hypotheses Estimation Problems Selection and Ranking Problems Computer Programs Sequential Probability Ratio Test Introduction Termination and Determination of A and B ASN Function and OC Function Examples and Implementation Auxiliary Results Sequential Tests for Composite Hypotheses Introduction Test for the Variance Test for the Mean Test for the Correlation Coefficient Test for the Gamma Shape Parameter Two-Sample Problem: Comparing the Means Auxiliary Results Sequential Nonparametric Tests Introduction A Test for the Mean: Known Variance A Test for the Mean: Unknown Variance A Test for the Percentile A Sign Test Data Analyses and Conclusions Estimation of the Mean of a Normal Population Introduction Fixed-Width Confidence Intervals Bounded Risk Point Estimation Minimum Risk Point Estimation Some Selected Derivations Location Estimation: Negative Exponential Distribution Introduction Fixed-Width Confidence Intervals Minimum Risk Point Estimation Selected Derivations Point Estimation of the Mean of an Exponential Population Introduction Minimum Risk Estimation Bounded Risk Estimation Data Analyses and Conclusions Other Selected Multistage Procedures Some Selected Derivations Fixed-Width Intervals from MLEs Introduction General Sequential Approach General Accelerated Sequential Approach Examples Data Analyses and Conclusions Some Selected Derivations Distribution-Free Methods in Estimation Introduction Fixed-Width Confidence Intervals for the Mean Minimum Risk Point Estimation for the Mean Bounded Length Confidence Interval for the Median Data Analyses and Conclusions Other Selected Multistage Procedures Some Selected Derivations Multivariate Normal Mean Vector Estimation Introduction Fixed-Size Confidence Region: SIGMA = sigma2H Fixed-Size Confidence Region: Unknown Dispersion Matrix Minimum Risk Point Estimation: Unknown Dispersion Matrix Data Analyses and Conclusions Other Selected Multistage Procedures Some Selected Derivations Estimation in a Linear Model Introduction Fixed-Size Confidence Region Minimum Risk Point Estimation Data Analyses and Conclusions Other Selected Multistage Procedures Some Selected Derivations Estimating the Difference of Two Normal Means Introduction Fixed-Width Confidence Intervals Minimum Risk Point Estimation Other Selected Multistage Procedures Some Selected Derivations Selecting the Best Normal Population Introduction Indifference Zone Formulation Two-Stage Procedure Sequential Procedure Data Analyses and Conclusions Other Selected Multistage Procedures Some Selected Derivations Sequential Bayesian Estimation Introduction Selected Fixed Sample Size Concepts Elementary Sequential Concepts Data Analysis Selected Applications Introduction Clinical Trials Integrated Pest Management Experimental Psychology: Cognition of Distance A Problem from Horticulture Other Contemporary Areas of Applications Appendix: Selected Reviews, Tables, and Other Items Introduction Big O(.) and Little o(.) Some Probabilistic Notions and Results A Glimpse at Nonlinear Renewal Theory Abbreviations and Notation Statistical Tables References Index Exercises appear at the end of each chapter.