SpringerBriefs in Statistics, JSS research series in statistics
یادداشتهای مربوط به کتابنامه ، واژه نامه و نمایه های داخل اثر
متن يادداشت
Includes bibliographical references and index.
یادداشتهای مربوط به مندرجات
متن يادداشت
Intro; Preface; Acknowledgements; Contents; Abbreviations; Notations; 1 Introduction to Double-Truncation; 1.1 Doubly Truncated Data; 1.2 Probability Models for Double-Truncation; 1.3 Truncation Bias; 1.4 Likelihood-Based Inference Under Double-Truncation; 1.4.1 Random Double-Truncation; 1.4.2 Fixed-Length Double-Truncation; 1.4.3 Maximum Likelihood Estimation; 1.4.4 Other Estimation Methods; 1.5 Relation to Censoring; References; 2 Parametric Estimation Under Exponential Family; 2.1 Introduction; 2.2 Special Exponential Family (SEF); 2.2.1 One-Parameter Models; 2.2.2 Two-Parameter Models
متن يادداشت
2.2.3 Cubic Models2.2.4 More Than Three Parameters; 2.3 Likelihood Function; 2.3.1 One-Parameter Models; 2.3.2 Two-Parameter Models; 2.3.3 Cubic Models; 2.4 The Newton-Raphson Algorithm; 2.4.1 One-Parameter Models; 2.4.2 Two-Parameter Models; 2.4.3 Cubic Models; 2.5 Asymptotic Theory; 2.6 An R Package "double.truncation"; 2.7 Data Analysis; 2.8 Additional Remarks; References; 3 Bayesian Inference for Doubly Truncated Data; 3.1 Introduction; 3.2 Bayesian Inference; 3.3 A Bayesian Model for Double-Truncation; 3.3.1 Birth Process; 3.3.2 Selection Probability
متن يادداشت
3.3.3 Homogeneous and Inhomogeneous Birth Processes3.3.4 Density of Observed Lifetimes; 3.3.5 Likelihood Function; 3.3.6 Identifiability; 3.3.7 Exponential Families as a Special Case; 3.4 Estimation; 3.4.1 Metropolis Algorithm; 3.5 Numerical Suggestions; 3.5.1 Numerical Determination of the Selection Probability; 3.5.2 Tuning the Metropolis Algorithm; 3.6 Application; References; 4 Nonparametric Inference for Double-Truncation; 4.1 Introduction; 4.2 Heuristic Derivation of the NPMLE of f; 4.3 Joint Maximum Likelihood Estimate of f and k; 4.4 Asymptotic Properties and Bootstrap Approximation
متن يادداشت
4.5 ApplicationReferences; 5 Linear Regression Under Random Double-Truncation; 5.1 Introduction; 5.2 Model and Method; 5.3 Properties of the Estimators; 5.4 Application; References; Appendix A Formula of the SE for the NPMLE; Appendix B Score Function and Hessian Matrix in a Two-Parameter Model; Appendix C R Codes for the Analysis of Childhood Cancer Data; Appendix D R Code for Bayesian Analysis of Doubly Truncated Data; Appendix E R Code for Non-parametric Analysis of Doubly Truncated Data; Appendix F R Code for Linear Regression Under Random Double Truncation; Index
بدون عنوان
0
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
This book introduces readers to statistical methodologies used to analyze doubly truncated data. The first book exclusively dedicated to the topic, it provides likelihood-based methods, Bayesian methods, non-parametric methods, and linear regression methods. These procedures can be used to effectively analyze continuous data, especially survival data arising in biostatistics and economics. Because truncation is a phenomenon that is often encountered in non-experimental studies, the methods presented here can be applied to many branches of science. The book provides R codes for most of the statistical methods, to help readers analyze their data. Given its scope, the book is ideally suited as a textbook for students of statistics, mathematics, econometrics, and other fields.
یادداشتهای مربوط به سفارشات
منبع سفارش / آدرس اشتراک
Springer Nature
شماره انبار
com.springer.onix.9789811362415
ویراست دیگر از اثر در قالب دیگر رسانه
عنوان
Analysis of Doubly Truncated Data : An Introduction.
شماره استاندارد بين المللي کتاب و موسيقي
9789811362408
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Mathematical statistics.
موضوع مستند نشده
Mathematical statistics.
مقوله موضوعی
موضوع مستند نشده
MAT029000
موضوع مستند نشده
PBT
موضوع مستند نشده
PBT
رده بندی ديویی
شماره
519
.
5
ويراست
23
رده بندی کنگره
شماره رده
QA276
نشانه اثر
.
D67
2019
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )