Maximum Penalized Likelihood Estimation
Maximum Penalized Likelihood Estimation

Author: Paul P. Eggermont

Publisher: Springer

Published: 2011-12-02

Total Pages: 0

ISBN-13: 9781461417125

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Unique blend of asymptotic theory and small sample practice through simulation experiments and data analysis. Novel reproducing kernel Hilbert space methods for the analysis of smoothing splines and local polynomials. Leading to uniform error bounds and honest confidence bands for the mean function using smoothing splines Exhaustive exposition of algorithms, including the Kalman filter, for the computation of smoothing splines of arbitrary order.

Maximum Penalized Likelihood Estimation
Maximum Penalized Likelihood Estimation

Author: P.P.B. Eggermont

Publisher: Springer Nature

Published: 2020-12-15

Total Pages: 514

ISBN-13: 1071612441

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This book deals with parametric and nonparametric density estimation from the maximum (penalized) likelihood point of view, including estimation under constraints. The focal points are existence and uniqueness of the estimators, almost sure convergence rates for the L1 error, and data-driven smoothing parameter selection methods, including their practical performance. The reader will gain insight into technical tools from probability theory and applied mathematics.

The Frailty Model
The Frailty Model

Author: Luc Duchateau

Publisher: Springer Science & Business Media

Published: 2007-10-23

Total Pages: 329

ISBN-13: 038772835X

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Readers will find in the pages of this book a treatment of the statistical analysis of clustered survival data. Such data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography. A typical example is the time to death in cancer patients, with patients clustered in hospitals. Frailty models provide a powerful tool to analyze clustered survival data. In this book different methods based on the frailty model are described and it is demonstrated how they can be used to analyze clustered survival data. All programs used for these examples are available on the Springer website.

Maximum Penalized Likelihood Estimation
Maximum Penalized Likelihood Estimation

Author: Paul P. Eggermont

Publisher: Springer Science & Business Media

Published: 2009-06-02

Total Pages: 580

ISBN-13: 0387689028

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Unique blend of asymptotic theory and small sample practice through simulation experiments and data analysis. Novel reproducing kernel Hilbert space methods for the analysis of smoothing splines and local polynomials. Leading to uniform error bounds and honest confidence bands for the mean function using smoothing splines Exhaustive exposition of algorithms, including the Kalman filter, for the computation of smoothing splines of arbitrary order.

Maximum Penalized Likelihood Estimation
Maximum Penalized Likelihood Estimation

Author: P.P.B. Eggermont

Publisher: Springer Science & Business Media

Published: 2001-06-21

Total Pages: 544

ISBN-13: 9780387952680

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This book deals with parametric and nonparametric density estimation from the maximum (penalized) likelihood point of view, including estimation under constraints. The focal points are existence and uniqueness of the estimators, almost sure convergence rates for the L1 error, and data-driven smoothing parameter selection methods, including their practical performance. The reader will gain insight into technical tools from probability theory and applied mathematics.

The Statistical Analysis of Interval-censored Failure Time Data
The Statistical Analysis of Interval-censored Failure Time Data

Author: Jianguo Sun

Publisher: Springer

Published: 2007-05-26

Total Pages: 310

ISBN-13: 0387371192

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This book collects and unifies statistical models and methods that have been proposed for analyzing interval-censored failure time data. It provides the first comprehensive coverage of the topic of interval-censored data and complements the books on right-censored data. The focus of the book is on nonparametric and semiparametric inferences, but it also describes parametric and imputation approaches. This book provides an up-to-date reference for people who are conducting research on the analysis of interval-censored failure time data as well as for those who need to analyze interval-censored data to answer substantive questions.

Introduction to Empirical Processes and Semiparametric Inference
Introduction to Empirical Processes and Semiparametric Inference

Author: Michael R. Kosorok

Publisher: Springer Science & Business Media

Published: 2007-12-29

Total Pages: 482

ISBN-13: 0387749780

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Kosorok’s brilliant text provides a self-contained introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods. This is an authoritative text that covers all the bases, and also a friendly and gradual introduction to the area. The book can be used as research reference and textbook.

Information Criteria and Statistical Modeling
Information Criteria and Statistical Modeling

Author: Sadanori Konishi

Publisher: Springer Science & Business Media

Published: 2008

Total Pages: 282

ISBN-13: 0387718869

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Statistical modeling is a critical tool in scientific research. This book provides comprehensive explanations of the concepts and philosophy of statistical modeling, together with a wide range of practical and numerical examples. The authors expect this work to be of great value not just to statisticians but also to researchers and practitioners in various fields of research such as information science, computer science, engineering, bioinformatics, economics, marketing and environmental science. It’s a crucial area of study, as statistical models are used to understand phenomena with uncertainty and to determine the structure of complex systems. They’re also used to control such systems, as well as to make reliable predictions in various natural and social science fields.