Density Estimation for Statistics and Data Analysis

Density Estimation for Statistics and Data Analysis presents a practical, accessible account of density estimation with the goal of facilitating broader practical application of density estimation and encouraging further research. The author discusses several applications, including the analysis and presentation of data, nonparametric discriminant analysis, cluster analysis, simulation and the bootstrap, bump hunting, projection pursuit, and the estimation of hazard rates. The book includes a general survey of methods available for density estimation and discusses the kernel method, adaptive methods, and methods based on penalized likelihood. More the 50 graphs and figures complement the text.

Zusatztext "This well-written and moderately priced volume has removed any excuse for ignorance concerning density estimation on the part of applied statisticians; they will find the style refreshingly down-to-earth! and will value the clearsighted exposition. I thoroughly enjoyed reading it! and can recommend it wholeheartedly."-Short Book Reviews"Highly recommended."-Choice Informationen zum Autor Silverman, Bernard. W. Klappentext The recent surge of interest in the more technical aspects ofdensity estimation has brought the subject into public view but has sadly created the impression! in some quarters! that density estimates are onlyoftheoreticalimportance.I have aimed in this book to make the subject accessible to a wider audience of statisticians and others! hoping to encouragebroaderpracticalapplication and more relevant theoretical research. With these objects in mind! I have tried to concentrate on topics of methodological interest. Specialists in the fieldwill!I am sure! notice omissionsofthe kind that are inevitable in a personal account; I hope in spite of these that they will find the treatment of the subject interesting and stimulating. I wouldliketo thank David Kendall for first kindling myinterest in density estimation. For their useful suggestions and other help I am grateful to several people! including Adrian Baddeley! Christopher Chatfield! David Cox! Rowena Fowler and Anthony Robinson. Colleagues who have helped in various specificwaysare acknowled­ ged in the course of the text. I am also grateful to the University of Washington (Seattle) for the opportunity to present a course of lectures that formed the basis of the book. Zusammenfassung An exposition of density estimation for statistics and data analysis. A volume in the "Monographs on Statistics and Applied Probability" series, it is designed for applied statisticians Inhaltsverzeichnis Introduction. Survey of Existing Methods. The Kernel Method for Univariate Data. The Kernel Method for Multivariate Data. Three Important Methods. Density Estimation in Action. ...

Autorentext
Silverman, Bernard. W.

Klappentext

The recent surge of interest in the more technical aspects ofdensity estimation has brought the subject into public view but has sadly created the impression, in some quarters, that density estimates are onlyoftheoreticalimportance.I have aimed in this book to make the subject accessible to a wider audience of statisticians and others, hoping to encouragebroaderpracticalapplication and more relevant theoretical research. With these objects in mind, I have tried to concentrate on topics of methodological interest. Specialists in the fieldwill,I am sure, notice omissionsofthe kind that are inevitable in a personal account; I hope in spite of these that they will find the treatment of the subject interesting and stimulating. I wouldliketo thank David Kendall for first kindling myinterest in density estimation. For their useful suggestions and other help I am grateful to several people, including Adrian Baddeley, Christopher Chatfield, David Cox, Rowena Fowler and Anthony Robinson. Colleagues who have helped in various specificwaysare acknowled­ ged in the course of the text. I am also grateful to the University of Washington (Seattle) for the opportunity to present a course of lectures that formed the basis of the book.

Zusammenfassung
An exposition of density estimation for statistics and data analysis. A volume in the "Monographs on Statistics and Applied Probability" series, it is designed for applied statisticians

Inhalt
Introduction. Survey of Existing Methods. The Kernel Method for Univariate Data. The Kernel Method for Multivariate Data. Three Important Methods. Density Estimation in Action.