Читать книгу The Statistical Analysis of Doubly Truncated Data - Prof Jacobo de Uña-Álvarez, Prof Carla Moreira - Страница 2

1  Cover

2  Title Page

3  Copyright

4  Dedication

5  Preface

6  List of Abbreviations

7  Notation

8  1 Introduction 1.1 Random Truncation 1.2 One‐sided Truncation 1.3 Double Truncation 1.4 Real Data Examples References

9  2 One‐Sample Problems 2.1 Nonparametric Estimation of a Distribution Function 2.2 Semiparametric and Parametric Approaches 2.3 R Code for the Examples References

10  3 Smoothing Methods 3.1 Some Background in Kernel Estimation 3.2 Estimating the Density Function 3.3 Asymptotic Properties 3.4 Data‐driven Bandwidth Selection 3.5 Further Issues in Kernel Density Estimation 3.6 Estimating the Hazard Function 3.7 R Code for the Examples References

11  4 Regression Analysis 4.1 Observational Bias in Regression 4.2 Proportional Hazards Regression 4.3 Accelerated Failure Time Regression 4.4 Nonparametric Regression 4.5 R Code for the Examples References

12  5 Further Topics 5.1 Two‐Sample Problems 5.2 Competing Risks 5.3 Testing for Quasi‐independence 5.4 Dependent Truncation 5.5 R Code for the Examples References

13  A: Packages and Functions in R A.1 Computing the NPMLE and Standard Errors A.2 Assessing the Existence and Uniqueness of the NPMLE A.3 Semiparametric and Parametric Estimation A.4 Kernel Estimation A.5 Regression Analysis A.6 Competing Risks A.7 Simulating Data A.8 Testing Quasi‐independence A.9 Dependent Truncation References

14  Index

15  End User License Agreement