Nonparametric Curve Estimation

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Nonparametric Curve Estimation

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Author : Sam Efromovich
language : en
Publisher: Springer Science & Business Media
Release Date : 1999-08-05

Nonparametric Curve Estimation written by Sam Efromovich and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-08-05 with Mathematics categories.

This book gives a systematic, comprehensive, and unified account of modern nonparametric statistics of density estimation, nonparametric regression, filtering signals, and time series analysis. The companion software package, available over the Internet, brings all of the discussed topics into the realm of interactive research. Virtually every claim and development mentioned in the book is illustrated with graphs which are available for the reader to reproduce and modify, making the material fully transparent and allowing for complete interactivity.

Nonparametric Curve Estimation From Time Series

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Author : Lazlo Gyorfi
language : en
Publisher:
Release Date : 2014-09-01

Nonparametric Curve Estimation From Time Series written by Lazlo Gyorfi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-01 with categories.

Nonparametric Curve Estimation

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Author : Sam Efromovich
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-01-19

Nonparametric Curve Estimation written by Sam Efromovich and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-19 with Mathematics categories.

This book gives a systematic, comprehensive, and unified account of modern nonparametric statistics of density estimation, nonparametric regression, filtering signals, and time series analysis. The companion software package, available over the Internet, brings all of the discussed topics into the realm of interactive research. Virtually every claim and development mentioned in the book is illustrated with graphs which are available for the reader to reproduce and modify, making the material fully transparent and allowing for complete interactivity.

Smoothing Techniques For Curve Estimation

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Author : T. Gasser
language : en
Publisher: Springer
Release Date : 2006-12-08

Smoothing Techniques For Curve Estimation written by T. Gasser and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-08 with Mathematics categories.

Nonparametric Curve Estimation

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Author : Sam Efromovich
language : en
Publisher:
Release Date : 2014-01-15

Nonparametric Curve Estimation written by Sam Efromovich and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.

Applied Nonparametric Regression

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Author : Wolfgang Härdle
language : en
Publisher: Cambridge University Press
Release Date : 1990

Applied Nonparametric Regression written by Wolfgang Härdle and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Business & Economics categories.

This is the first book to bring together in one place the techniques for regression curve smoothing involving more than one variable.

Nonparametric Econometrics

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Author : Qi Li
language : en
Publisher: Princeton University Press
Release Date : 2011-10-09

Nonparametric Econometrics written by Qi Li and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-09 with Business & Economics categories.

A comprehensive, up-to-date textbook on nonparametric methods for students and researchers Until now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook help make it the ideal introduction for graduate students and an indispensable resource for researchers. Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data—nominal and ordinal—in applied settings. The conventional nonparametric approach to dealing with the presence of discrete variables is acknowledged to be unsatisfactory. This book is tailored to the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types—continuous, nominal, and ordinal—within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables. Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems.

Nonparametric Curve Estimation From Time Series

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Author : László Györfi
language : en
Publisher:
Release Date : 1989

Nonparametric Curve Estimation From Time Series written by László Györfi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Estimation theory categories.

Kernel Smoothing

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Author : M.P. Wand
language : en
Publisher: CRC Press
Release Date : 1994-12-01

Kernel Smoothing written by M.P. Wand and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-12-01 with Mathematics categories.

Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. The basic principle is that local averaging or smoothing is performed with respect to a kernel function. This book provides uninitiated readers with a feeling for the principles, applications, and analysis of kernel smoothers. This is facilita