Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations (Oxford Statistical Science Series)

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9780198523963: Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations (Oxford Statistical Science Series)
Críticas:

...a well-written book that fills an obvious gap in the statistics literature...a pragmatic introduction to the application of smoothing methods. The book's layout and structure are well designed and its language lucid. Examples are drawn from a range of disciplines and should appeal to a broad readership...Statisticians, who are familiar with applied non-parametric smoothing through programmed uncertainty estimates may want to check this book anyway for the odd trick they may have missed. For anyone who lacks one or more of those elements, and is involved in any way with data analysis, it is an excellent buy. ( Scientific Computing World, April 1998)

A well-written book that fills an obvious gap in the statistics literature.....a pragmatic introduction to the application of smoothing methods. The book's layout and structure are well designed and its language lucid. Examples are drawn from a range of disciplines and should appeal to a broad readership.....an excellent buy. ( Scienctific Computing World)

This must be a very attractive book: when it was lying on my desk while preparing this review, it constantly taken away by students and colleagues who were attracted by the topic and the nice presentation with graphics, examples, S-Plus material, etc....A glance at the more than two-hundred references reveals that most of them date from the nineties and hence it becomes clear that this is an up-to-date book with the most recent state of the art. ( N. Veraverbeke, Short Book Reviews, August 1998)

There is a rich choice of examples, exercises, hints for further reading and S-Plus illustrations. Compared to the several other recent books in the area, the present monograph has the advantage of being introductory and practcial within a very reasonable number of pages.

Críticas:

"An up-to-date book with the most recent state of the art. . . . Accessible to nonmathematical readers. . .There is a rich choice of examples, exercises, hints for further reading and S-Plus illustrations." --N. Veraverbeke, Limburgs Universitair Centrum, Diepenbeek, Belgium"[T]his book provides an overview of smoothing techniques used in data analysis, with emphasis on one- and two-dimensional data. The authors' aim is to complement the existing books by focusing on intuitive presentation of the ideas and on practical issues of inference rather than estimation. The book consists of eight chapters and 193 pages, with the first two chapters devoted to density estimation and the last six . . . concentrating on smoothing in regression and time series. Real data are used throughout to illustrate the techniques. . . . [T]he book attempts to be both a practical introduction to smoothing and an outline of the methodological and theoretical development of the subject. It does reasonabl

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Bowman, Adrian W, Azzalini, Adelchi
Editorial: Oxford University Press (2017)
ISBN 10: 0198523963 ISBN 13: 9780198523963
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Descripción Oxford University Press, 2017. Hardcover. Estado de conservación: New. This item is printed on demand. Nº de ref. de la librería P110198523963

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Bowman, Adrian W; Azzalini, Adelchi
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Descripción Oxford University Press, 1997. Hardcover. Estado de conservación: New. book. Nº de ref. de la librería 0198523963

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Bowman, A. W.
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Descripción OUP Oxford, 2016. Paperback. Estado de conservación: New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. Nº de ref. de la librería ria9780198523963_lsuk

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Descripción Oxford University Press, United Kingdom, 1997. Hardback. Estado de conservación: New. 234 x 155 mm. Language: English . Brand New Book ***** Print on Demand *****.The book describes the use of smoothing techniques in statistics, including both density estimation and nonparametric regression. Considerable advances in research in this area have been made in recent years. The aim of this text is to describe a variety of ways in which these methods can be applied to practical problems in statistics. The role of smoothing techniques in exploring data graphically is emphasised, but the use of nonparametric curves in drawing conclusions from data, as an extension of more standard parametric models, is also a major focus of the book. Examples are drawn from a wide range of applications. The book is intended for those who seek an introduction to the area, with an emphasis on applications rather than on detailed theory. It is therefore expected that the book will benefit those attending courses at an advanced undergraduate, or postgraduate, level, as well as researchers, both from statistics and from other disciplines, who wish to learn about and apply these techniques in practical data analysis. The text makes extensive reference to S-Plus, as a computing environment in which examples can be explored. S-Plus functions and example scripts are provided to implement many of the techniques described. These parts are, however, clearly separate from the main body of text, and can therefore easily be skipped by readers not interested in S-Plus. Nº de ref. de la librería APC9780198523963

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A.W. Bowman, Adelchi Azzalini
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ISBN 10: 0198523963 ISBN 13: 9780198523963
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Descripción Oxford University Press, United Kingdom, 1997. Hardback. Estado de conservación: New. 234 x 155 mm. Language: English . Brand New Book ***** Print on Demand *****. The book describes the use of smoothing techniques in statistics, including both density estimation and nonparametric regression. Considerable advances in research in this area have been made in recent years. The aim of this text is to describe a variety of ways in which these methods can be applied to practical problems in statistics. The role of smoothing techniques in exploring data graphically is emphasised, but the use of nonparametric curves in drawing conclusions from data, as an extension of more standard parametric models, is also a major focus of the book. Examples are drawn from a wide range of applications. The book is intended for those who seek an introduction to the area, with an emphasis on applications rather than on detailed theory. It is therefore expected that the book will benefit those attending courses at an advanced undergraduate, or postgraduate, level, as well as researchers, both from statistics and from other disciplines, who wish to learn about and apply these techniques in practical data analysis. The text makes extensive reference to S-Plus, as a computing environment in which examples can be explored. S-Plus functions and example scripts are provided to implement many of the techniques described. These parts are, however, clearly separate from the main body of text, and can therefore easily be skipped by readers not interested in S-Plus. Nº de ref. de la librería APC9780198523963

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Bowman, Adrian W
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Descripción Oxford University Press, 2017. Hardcover. Estado de conservación: New. This item is printed on demand. Nº de ref. de la librería 0198523963

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Bowman, A. W.; Bowman, Azzalini; Bowman, Adrian W.
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Descripción Estado de conservación: New. This item is Print on Demand - Depending on your location, this item may ship from the US or UK. Nº de ref. de la librería POD_9780198523963

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Adrian W Bowman
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Descripción OUP Oxford. Hardcover. Estado de conservación: New. Hardcover. 208 pages. Dimensions: 9.2in. x 6.1in. x 0.7in.This book describes the use of smoothing techniques in statistics and includes both density estimation and nonparametric regression. Incorporating recent advances, it describes a variety of ways to apply these methods to practical problems. Although the emphasis is on using smoothing techniques to explore data graphically, the discussion also covers data analysis with nonparametric curves, as an extension of more standard parametric models. Intended as an introduction, with a focus on applications rather than on detailed theory, the book will be equally valuable for undergraduate and graduate students in statistics and for a wide range of scientists interested in statistical techniques. The text makes extensive reference to S-Plus, a powerful computing environment for exploring data, and provides many S-Plus functions and example scripts. This material, however, is independent of the main body of text and may be skipped by readers not interested in S-Plus. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Hardcover. Nº de ref. de la librería 9780198523963

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