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Statistical Models Based on Counting ProcessesPDF|Epub|txt|kindle电子书版本网盘下载
- 著
- 出版社： 世界图书出版公司北京公司
- ISBN：7506238179
- 出版时间：1998
- 标注页数：767页
- 文件大小：165MB
- 文件页数：779页
- 主题词：
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图书目录
Ⅰ．Introduction1
Ⅰ.1 General Introduction to the Book1
Ⅰ.2 Brief Survey of the Development of the Subject6
Ⅰ.3 Presentation of Practical Examples10
Ⅱ．The Mathematical Background45
Ⅱ.1 An Informal Introduction to the Basic Concepts48
Ⅱ.2 Preliminaries:Processes,Filtrations,and Stopping Times59
Ⅱ.3 Martingale Theory64
Ⅱ.4 Counting Processes72
Ⅱ.5 Limit Theory82
Ⅱ.6 Product-Integration and Markov Processes88
Ⅱ.7 Likelihoods and Partial Likelihoods for Counting Processes95
Ⅱ.8 The Functional Delta-Method109
Ⅱ.9 Bibliographic Remarks115
Ⅲ．Model Specification and Censoring121
Ⅲ.1 Examples of Counting Process models for Complete Life History Data.The Multiplicative Intensity Model122
Ⅲ.2 Right-Censoring135
Ⅲ.3 Left-Truncation152
Ⅲ.4 General Censorship,Filtering,and Truncation161
Ⅲ.5 Partial Model Specification.Time-Dependent Covariates168
Ⅲ.6 Bibliographic Remarks172
Ⅳ．Nonparametric Estimation176
Ⅳ.1 The Nelson-Aalen estimator177
Ⅳ.2 Smoothing the Nelson-Aalen Estimator229
Ⅳ.3 The Kaplan-Meier Estimator255
Ⅳ.4 The Product-Limit Estimator for the Transition Matrix of a Nonhomogeneous Markov Process287
Ⅳ.5 Bibliographic Remarks321
Ⅴ．Nonparametric Hypothesis Testing332
Ⅴ.1 One-Sample Tests333
Ⅴ.2 k-Sample Tests345
Ⅴ.3 Other Linear Nonparametric Tests379
Ⅴ.4 Using the Complete Test Statistic Process390
Ⅴ.5 Bibliographic Remarks397
Ⅵ．Parametric Models401
Ⅵ.1 Maximum Likelihood Estimation402
Ⅵ.2 M-Estimators433
Ⅵ.3 Model Checking444
Ⅵ.4 Bibliographic Remarks471
Ⅶ．Regression Models476
Ⅶ.1 Introduction.Regression Model Formulation476
Ⅶ.2 Semiparametric Multiplicative Hazard Models481
Ⅶ.3 Goodness-of-Fit Methods for the Semiparametric Multiplicative Hazard Model539
Ⅶ.4 Nonparametric Additive Hazard Models562
Ⅶ.5 Other Non-and Semi-parametric Regression Models578
Ⅶ.6 Parametric Regression Models583
Ⅶ.7 Bibliographic Remarks588
Ⅷ．Asymptotic Efficiency592
Ⅷ.1 Contiguity andLocal Asymptotic Normality594
Ⅷ.2 Local Asymptotic Normality in Counting Process Models607
Ⅷ.3 Infinite-dimensional Parameter Spaces:the General Theory627
Ⅷ.4 Semiparametric Counting Process Models635
Ⅷ.5 Bibliographic Remarks656
Ⅸ．Frailty Models660
Ⅸ.1 Introduction660
Ⅸ.2 Model Construction662
Ⅸ.3 Likelihoods and Intensities664
Ⅸ.4 Parametric and Nonparametric Maximum Likelihood Estimation with the EM-Algorithm667
Ⅸ.5 Bibliographic Remarks673
Ⅹ．Multivariate Time Scales675
Ⅹ.1 Examples of Several Time Scales676
Ⅹ.2 Sequential Analysis of Censored Survival Data with Staggered Entry683
Ⅹ.3 Nonparametric Estimation of the Multivariate Survival Function688
Ⅹ.4 Bibliographic Remarks706
Appendix The Melanoma Survival Data and Standard Mortality Tables for the Danish Population 1971-75709
References715
Author Index747
Subject Index755