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Nonparametric and Semiparametric Models, Hardcover by Hardle, Wolfgang; Mulle...
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Item specifics
- Condition
- Book Title
- Nonparametric and Semiparametric Models
- ISBN
- 9783540207221
- Publication Name
- Nonparametric and Semiparametric Models
- Item Length
- 9.3in
- Publisher
- Springer Berlin / Heidelberg
- Series
- Springer Series in Statistics Ser.
- Publication Year
- 2004
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Height
- 0.4in
- Item Width
- 6.1in
- Item Weight
- 23.4 Oz
- Number of Pages
- Xxvii, 300 Pages
About this product
Product Information
The concept of smoothing is a central idea in statistics. Its role is to extract structural elements of variable complexity from patterns of random var- tion. The nonparametric smoothing concept is designed to simultaneously estimate and model the underlying structure. This involves high dim- sionalobjects,likedensityfunctions,regressionsurfacesorconditionalqu- tiles. Such objects are dif'cult to estimate for data sets with mixed, high - mensional and partially unobservable variables. The semiparametric mod- ing technique compromises the two aims, ?exibility and simplicity of stat- tical procedures, by introducing partial parametric components. These (low dimensional) components allow one to match structural conditions like for example linearity in some variables and may be used to model the in'uence of discrete variables. The ?exibility of semiparametric modeling has made it a widely accepted statistical technique. The aim of this monograph is to present the statistical and mathematical principles of smoothing with a focus on applicable techniques. The necessary mathematical treatment is easily understandable and a wide variety of int- active smoothing examples are given. This text is an e-book; it is a downlo- able entity (http://www. i-xplore. de) which allows the reader to recalculate all arguments and applications without reference to a speci'c software pl- form. This new technique for proliferation of methods and ideas is spec- cally designed for the beginner in nonparametric and semiparametric stat- tics. It is based on the XploRe quantlet technology, developed at Humboldt- Universitat ¨ zu Berlin.
Product Identifiers
Publisher
Springer Berlin / Heidelberg
ISBN-10
3540207228
ISBN-13
9783540207221
eBay Product ID (ePID)
30751972
Product Key Features
Publication Name
Nonparametric and Semiparametric Models
Format
Hardcover
Language
English
Series
Springer Series in Statistics Ser.
Publication Year
2004
Type
Textbook
Number of Pages
Xxvii, 300 Pages
Dimensions
Item Length
9.3in
Item Height
0.4in
Item Width
6.1in
Item Weight
23.4 Oz
Additional Product Features
Number of Volumes
1 Vol.
Lc Classification Number
Qa273.A1-274.9
Reviews
From the reviews:"This book contains a good coverage of some of the widely used nonparametric and semiparametric modeling techniques. … The concepts are presented very clearly with numerous examples and data analytic illustrations. … Authors have done a good job of illustrating the concepts and the methodology with very well chosen examples. The exercises at the end of each chapter are carefully prepared so that students become familiar with the important issues. This book will be very useful for students in statistics, biostatistics and econometrics." (Probal Chaudhuri, Sankhya, Vol. 67 (1), 2005)"This is another book by Professor Wolfgang Härdle and his colleagues on nonparametric statistics and smoothing. The unique feature of this book is the inclusion of topics on semi-parametric regression models for high-dimensional data. … Minimum theory and numerical examples are covered in this book, which makes this book mostly suitable for a course in nonparametric regression to graduate students. … will be useful for readers who would like to understand the statistical and mathematical principles and basic concepts and techniques of smoothing." (Dongsheng Tu, Zentralblatt MATH, Vol. 1059 (10), 2005)"This book deals with the problem of how to estimate … . As such the problems that it deals with are closely related to the exploratory data analysis techniques … . The text is well organized, with some exercises, which in the later sections of the book have the character of research theses. Each chapter ends with a useful summary, and the notation is summarized at the beginning of the book. … would be good for those wanting to catch up with recent developments in this field." (Mark P. Little, Journal of the Royal Statistical Society, Vol. 168 (4), 2005)"The book is very well written and a pleasure to read with the methods fully illustrated. At the end of each chapter is a valuable summary of the important formulae and methods introduced in the chapter. The book progresses by first motivating, then developing methodology, and finally providing statistical properties." (T.P. Hettmansperger, Short Book Reviews, Vol. 24 (3), 2004)"This book, part of the Springer Series in Statistics, is a detailed, mathematical presentation of smoothing techniques … . Each chapter ends with a summary of key issues and findings that were presented earlier and serves as an excellent review for the reader. Finally, bibliographic notes at the end of each chapter often provide good historic perspective … . This book is a thorough and complete reference on modeling techniques … . a useful source on the theory associated with smoothing algorithms and testing." (Robert Lordo, Technometrics, Vol. 47 (2), May, 2005) , From the reviews: "This book contains a good coverage of some of the widely used nonparametric and semiparametric modeling techniques. ... The concepts are presented very clearly with numerous examples and data analytic illustrations. ... Authors have done a good job of illustrating the concepts and the methodology with very well chosen examples. The exercises at the end of each chapter are carefully prepared so that students become familiar with the important issues. This book will be very useful for students in statistics, biostatistics and econometrics." (Probal Chaudhuri, Sankhya, Vol. 67 (1), 2005) "This is another book by Professor Wolfgang Hrdle and his colleagues on nonparametric statistics and smoothing. The unique feature of this book is the inclusion of topics on semi-parametric regression models for high-dimensional data. ... Minimum theory and numerical examples are covered in this book, which makes this book mostly suitable for a course in nonparametric regression to graduate students. ... will be useful for readers who would like to understand the statistical and mathematical principles and basic concepts and techniques of smoothing." (Dongsheng Tu, Zentralblatt MATH, Vol. 1059 (10), 2005) "This book deals with the problem of how to estimate ... . As such the problems that it deals with are closely related to the exploratory data analysis techniques ... . The text is well organized, with some exercises, which in the later sections of the book have the character of research theses. Each chapter ends with a useful summary, and the notation is summarized at the beginning of the book. ... would be good for those wanting to catch up with recent developments in this field." (Mark P. Little, Journal of the Royal Statistical Society, Vol. 168 (4), 2005) "The book is very well written and a pleasure to read with the methods fully illustrated. At the end of each chapter is a valuable summary of the important formulae and methods introduced in the chapter. The book progresses by first motivating, then developing methodology, and finally providing statistical properties." (T.P. Hettmansperger, Short Book Reviews, Vol. 24 (3), 2004) "This book, part of the Springer Series in Statistics, is a detailed, mathematical presentation of smoothing techniques ... . Each chapter ends with a summary of key issues and findings that were presented earlier and serves as an excellent review for the reader. Finally, bibliographic notes at the end of each chapter often provide good historic perspective ... . This book is a thorough and complete reference on modeling techniques ... . a useful source on the theory associated with smoothing algorithms and testing." (Robert Lordo, Technometrics, Vol. 47 (2), May, 2005), From the reviews: "This book contains a good coverage of some of the widely used nonparametric and semiparametric modeling techniques. ... The concepts are presented very clearly with numerous examples and data analytic illustrations. ... Authors have done a good job of illustrating the concepts and the methodology with very well chosen examples. The exercises at the end of each chapter are carefully prepared so that students become familiar with the important issues. This book will be very useful for students in statistics, biostatistics and econometrics." (Probal Chaudhuri, Sankhya, Vol. 67 (1), 2005) "This is another book by Professor Wolfgang Härdle and his colleagues on nonparametric statistics and smoothing. The unique feature of this book is the inclusion of topics on semi-parametric regression models for high-dimensional data. ... Minimum theory and numerical examples are covered in this book, which makes this book mostly suitable for a course in nonparametric regression to graduate students. ... will be useful for readers who would like to understand the statistical and mathematical principles and basic concepts and techniques of smoothing." (Dongsheng Tu, Zentralblatt MATH, Vol. 1059 (10), 2005) "This book deals with the problem of how to estimate ... . As such the problems that it deals with are closely related to the exploratory data analysis techniques ... . The text is well organized, with some exercises, which in the later sections of the book have the character of research theses. Each chapter ends with a useful summary, and the notation is summarized at the beginning of the book. ... would be good for those wanting to catch up with recent developments in this field." (Mark P. Little, Journal of the Royal Statistical Society, Vol. 168 (4), 2005) "The book is very well written and a pleasure to read with the methods fully illustrated. At the end of each chapter is a valuable summary of the important formulae and methods introduced in the chapter. The book progresses by first motivating, then developing methodology, and finally providing statistical properties." (T.P. Hettmansperger, Short Book Reviews, Vol. 24 (3), 2004) "This book, part of the Springer Series in Statistics, is a detailed, mathematical presentation of smoothing techniques ... . Each chapter ends with a summary of key issues and findings that were presented earlier and serves as an excellent review for the reader. Finally, bibliographic notes at the end of each chapter often provide good historic perspective ... . This book is a thorough and complete reference on modeling techniques ... . a useful source on the theory associated with smoothing algorithms and testing." (Robert Lordo, Technometrics, Vol. 47 (2), May, 2005), From the reviews: "This book contains a good coverage of some of the widely used nonparametric and semiparametric modeling techniques. ... The concepts are presented very clearly with numerous examples and data analytic illustrations. ... Authors have done a good job of illustrating the concepts and the methodology with very well chosen examples. The exercises at the end of each chapter are carefully prepared so that students become familiar with the important issues. This book will be very useful for students in statistics, biostatistics and econometrics." (Probal Chaudhuri, Sankhya, Vol. 67 (1), 2005) "This is another book by Professor Wolfgang Härdle and his colleagues on nonparametric statistics and smoothing. The unique feature of this book is the inclusion of topics on semi-parametric regression models for high-dimensional data. ... Minimum theory and numerical examples are covered in this book, which makes this book mostly suitable for a course in nonparametric regression to graduate students. ... will be useful for readers who would like to understand the statistical and mathematical principles and basic concepts and techniques of smoothing." (Dongsheng Tu, Zentralblatt MATH, Vol. 1059 (10), 2005) "This book deals with the problem of how to estimate ... . As such the problems that it deals with are closely related to the exploratory data analysis techniques ... . The text is well organized, with some exercises, which in the later sections of the book have the character of research theses. Each chapter ends with a useful summary, and the notation is summarized at the beginning of the book. ... would be good for those wanting to catch up with recent developments in this field." (Mark P. Little, Journal of the Royal Statistical Society, Vol. 168 (4), 2005) "The book is very well written and a pleasure to read with the methods fully illustrated. At the end of each chapter is a valuable summary of the important formulae andmethods introduced in the chapter. The book progresses by first motivating, then developing methodology, and finally providing statistical properties." (T.P. Hettmansperger, Short Book Reviews, Vol. 24 (3), 2004) "This book, part of the Springer Series in Statistics, is a detailed, mathematical presentation of smoothing techniques ... . Each chapter ends with a summary of key issues and findings that were presented earlier and serves as an excellent review for the reader. Finally, bibliographic notes at the end of each chapter often provide good historic perspective ... . This book is a thorough and complete reference on modeling techniques ... . a useful source on the theory associated with smoothing algorithms and testing." (Robert Lordo, Technometrics, Vol. 47 (2), May, 2005), From the reviews: "This book contains a good coverage of some of the widely used nonparametric and semiparametric modeling techniques. ... The concepts are presented very clearly with numerous examples and data analytic illustrations. ... Authors have done a good job of illustrating the concepts and the methodology with very well chosen examples. The exercises at the end of each chapter are carefully prepared so that students become familiar with the important issues. This book will be very useful for students in statistics, biostatistics and econometrics." (Probal Chaudhuri, Sankhya, Vol. 67 (1), 2005) "This is another book by Professor Wolfgang Härdle and his colleagues on nonparametric statistics and smoothing. The unique feature of this book is the inclusion of topics on semi-parametric regression models for high-dimensional data. ... Minimum theory and numerical examples are covered in this book, which makes this book mostly suitable for a course in nonparametric regression to graduate students. ... will be useful for readers who would like to understand the statistical and mathematical principles and basic concepts and techniques of smoothing." (Dongsheng Tu, Zentralblatt MATH, Vol. 1059 (10), 2005) "This book deals with the problem of how to estimate ... . As such the problems that it deals with are closely related to the exploratory data analysis techniques ... . The text is well organized, with some exercises, which in the later sections of the book have the character of research theses. Each chapter ends with a useful summary, and the notation is summarized at the beginning of the book. ... would be good for those wanting to catch up with recent developments in this field." (Mark P. Little, Journal of the Royal Statistical Society, Vol. 168 (4), 2005) "The book is very well written and a pleasure to read with the methods fully illustrated. At the end of each chapter is a valuable summary of the important formulae and methods introduced in the chapter. The book progresses by first motivating, then developing methodology, and finally providing statistical properties." (T.P. Hettmansperger, Short Book Reviews, Vol. 24 (3), 2004) "This book, part of the Springer Series in Statistics, is a detailed, mathematical presentation of smoothing techniques ... . Each chapter ends with a summary of key issues and findings that were presented earlier and serves as an excellent review for the reader. Finally, bibliographic notes at the end of each chapter often provide good historic perspective ... . This book is a thorough and complete reference on modeling techniques ... . a useful source on the theory associated with smoothing algorithms and testing." (Robert Lordo, Technometrics, Vol. 47 (2), May, 2005) , From the reviews: "This book contains a good coverage of some of the widely used nonparametric and semiparametric modeling techniques. … The concepts are presented very clearly with numerous examples and data analytic illustrations. … Authors have done a good job of illustrating the concepts and the methodology with very well chosen examples. The exercises at the end of each chapter are carefully prepared so that students become familiar with the important issues. This book will be very useful for students in statistics, biostatistics and econometrics." (Probal Chaudhuri, Sankhya, Vol. 67 (1), 2005) "This is another book by Professor Wolfgang Härdle and his colleagues on nonparametric statistics and smoothing. The unique feature of this book is the inclusion of topics on semi-parametric regression models for high-dimensional data. … Minimum theory and numerical examples are covered in this book, which makes this book mostly suitable for a course in nonparametric regression to graduate students. … will be useful for readers who would like to understand the statistical and mathematical principles and basic concepts and techniques of smoothing." (Dongsheng Tu, Zentralblatt MATH, Vol. 1059 (10), 2005) "This book deals with the problem of how to estimate … . As such the problems that it deals with are closely related to the exploratory data analysis techniques … . The text is well organized, with some exercises, which in the later sections of the book have the character of research theses. Each chapter ends with a useful summary, and the notation is summarized at the beginning of the book. … would be good for those wanting to catch up with recent developments in this field." (Mark P. Little, Journal of the Royal Statistical Society, Vol. 168 (4), 2005) "The book is very well written and a pleasure to read with the methods fully illustrated. At the end of each chapter is a valuable summary of the important formulae and methods introduced in the chapter. The book progresses by first motivating, then developing methodology, and finally providing statistical properties." (T.P. Hettmansperger, Short Book Reviews, Vol. 24 (3), 2004) "This book, part of the Springer Series in Statistics, is a detailed, mathematical presentation of smoothing techniques … . Each chapter ends with a summary of key issues and findings that were presented earlier and serves as an excellent review for the reader. Finally, bibliographic notes at the end of each chapter often provide good historic perspective … . This book is a thorough and complete reference on modeling techniques … . a useful source on the theory associated with smoothing algorithms and testing." (Robert Lordo, Technometrics, Vol. 47 (2), May, 2005), From the reviews: "This book contains a good coverage of some of the widely used nonparametric and semiparametric modeling techniques. a? The concepts are presented very clearly with numerous examples and data analytic illustrations. a? Authors have done a good job of illustrating the concepts and the methodology with very well chosen examples. The exercises at the end of each chapter are carefully prepared so that students become familiar with the important issues. This book will be very useful for students in statistics, biostatistics and econometrics." (Probal Chaudhuri, Sankhya, Vol. 67 (1), 2005) "This is another book by Professor Wolfgang H'rdle and his colleagues on nonparametric statistics and smoothing. The unique feature of this book is the inclusion of topics on semi-parametric regression models for high-dimensional data. a? Minimum theory and numerical examples are covered in this book, which makes this book mostly suitable for a course in nonparametric regression to graduate students. a? will be useful for readers who would like to understand the statistical and mathematical principles and basic concepts and techniques of smoothing." (Dongsheng Tu, Zentralblatt MATH, Vol. 1059 (10), 2005) "This book deals with the problem of how to estimate a? . As such the problems that it deals with are closely related to the exploratory data analysis techniques a? . The text is well organized, with some exercises, which in the later sections of the book have the character of research theses. Each chapter ends with a useful summary, and the notation is summarized at the beginning of the book. a? would be good for those wanting to catch up with recent developments in this field." (Mark P. Little, Journal of the Royal Statistical Society, Vol. 168 (4), 2005) "The book is very well written and a pleasure to read with the methods fully illustrated. At the end of each chapter is a valuable summary of the important formulae and methods introduced in the chapter. The book progresses by first motivating, then developing methodology, and finally providing statistical properties." (T.P. Hettmansperger, Short Book Reviews, Vol. 24 (3), 2004) "This book, part of the Springer Series in Statistics, is a detailed, mathematical presentation of smoothing techniques a? . Each chapter ends with a summary of key issues and findings that were presented earlier and serves as an excellent review for the reader. Finally, bibliographic notes at the end of each chapter often provide good historic perspective a? . This book is a thorough and complete reference on modeling techniques a? . a useful source on the theory associated with smoothing algorithms and testing." (Robert Lordo, Technometrics, Vol. 47 (2), May, 2005)
Table of Content
1 Introduction.- 1.1 Density Estimation.- 1.2 Regression.- Summary.- I Nonparametric Models.- 2 Histogram.- 3 Nonparametric Density Estimation.- 4 Nonparametric Regression.- II Semiparametric Models.- 5 Semiparametric and Generalized Regression Models.- 6 Single Index Models.- 7 Generalized Partial Linear Models.- 8 Additive Models and Marginal Effects.- 9 Generalized Additive Models.- References.- Author Index.
Copyright Date
2004
Topic
Probability & Statistics / General, General, Econometrics, Statistics
Lccn
2004-556084
Intended Audience
Scholarly & Professional
Illustrated
Yes
Genre
Business & Economics, Mathematics
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