Overview
- Fully develops the theory of convex minimization problems to obtain convergence rates
- Includes simulation studies and analyses of classical data sets using fully automatic (data driven) procedures
- Many topics appear for the first time in textbook form
- Intended for graduate students as well as researchers and practitioners in the field of statistics and industrial mathematics
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Series in Statistics (SSS)
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Table of contents (12 chapters)
Keywords
About this book
Reviews
From the reviews:
“This book is meant for specialized readers or graduate students interested in the theory, computation and application of Nonparametric Regression to real data, and the new contributions of the authors. … For mathematically mature readers, the book would be a delight to read. … The authors have not only written a scholarly and very readable book but provide major new methods and insights. … it would help evaluate the methods as well as lead to teachable notes for a graduate course.” (Jayanta K. Ghosh, International Statistical Review, Vol. 79 (1), 2011)
“This book is the second volume of a three-volume textbook in the Springer Series in Statistics. … The second volume also belongs to the literature on nonparametric statistical inference and concentrates mainly on nonparametric regression. … The book can be used for two main purposes: as a textbook for M.S./Ph.D. students in statistics, operations research, and applied mathematics, and as a tool for researchers and  practitioners in these fields who want to develop and to apply nonparametric regression methods.” (Yurij S. Kharin, Mathematical Reviews, Issue 2012 g)
Bibliographic Information
Book Title: Maximum Penalized Likelihood Estimation
Book Subtitle: Volume II: Regression
Authors: Vincent N. LaRiccia, Paul P. Eggermont
Series Title: Springer Series in Statistics
DOI: https://doi.org/10.1007/b12285
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag New York 2009
Hardcover ISBN: 978-0-387-40267-3Published: 06 July 2009
Softcover ISBN: 978-1-4614-1712-5Published: 02 December 2011
eBook ISBN: 978-0-387-68902-9Published: 02 June 2009
Series ISSN: 0172-7397
Series E-ISSN: 2197-568X
Edition Number: 1
Number of Pages: XX, 572
Topics: Probability Theory and Stochastic Processes, Statistical Theory and Methods, Biometrics, Econometrics, Signal, Image and Speech Processing, Biostatistics