《大樣本理論基礎(chǔ)(英文版)》在講述一階大樣本理論方面比較獨(dú)特，討論了大量的應(yīng)用，包括密度估計(jì)、自助法和抽樣方法論的漸進(jìn)�！洞髽颖纠碚摶A(chǔ)(英文版)》的內(nèi)容比較基礎(chǔ)，適合統(tǒng)計(jì)專(zhuān)業(yè)的研究生和有兩年微積分背景的應(yīng)用領(lǐng)域。每章末有針對(duì)本章每節(jié)的問(wèn)題和練習(xí)，每節(jié)末都附有小結(jié)。
目錄：
Preface
1 Mathematical Background
1.1 The concept of limit
1.2 Embedding sequences
1.3 Infinite series
1.4 Order relations and rates of convergence
1.5 Continuity
1.6 Distributions
1.7 Problems
2 Convergence in Probability and in Law
2.1 Convergence in probability
2.2 Applications
2.3 Convergence in law
2.4 The central limit theorem
2.5 Taylor's theorem and the delta method
2.6 Uniform convergence
2.7 The CLT for independent non-identical random variables
2.8 Central limit theorem for dependent variables
2.9 Problems
3 Performance of Statistical Tests
.3.1 Critical values
3.2 Comparing two treatments
3.3 Power and sample size
3.4 Comparison of tests: Relative efficiency
3.5 Robustness
3.6 Problems
4 Estimation
4.1 Confidence intervals
4.2 Accuracy of point estimators
4.3 Comparing estimators
4.4 Sampling from a finite population
4.5 Problems
5 Multivariate Extensions
5.1 Convergence of multivariate distributions
5.2 The bivariate normal distribution
5.3 Some linear algebra
5.4 The multivariate normal distribution
5.5 Some applications
5.6 Estimation and testing in 2 × 2 tables
5.7 Testing goodness of fit
5.8 Problems
6 Nonparametric Estimation
6.1 U-Statistics
6.2 Statistical functionals
6.3 Limit distributions of statistical functionals
6.4 Density estimation
6.5 Bootstrapping
6.6 Problems
7 Efficient Estimators and Tests
7.1 Maximum likelihood
7.2 Fisher information
7.3 Asymptotic normality and multiple roots
7.4 Efficiency
7.5 The multiparameter case I. Asymptotic normality
7.6 The multiparameter case II. Efficiency
7.7 Tests and confidence intervals
7.8 Contingency tables
7.9 Problems
Appendix
References
Author Index
Subject Index
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