Nonparametric Estimation Of Probability Densities And Regression Curves
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Nonparametric Estimation Of Probability Densities And Regression Curves
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Author : Nadaraya
language : en
Publisher: Springer
Release Date : 1988-12-31
Nonparametric Estimation Of Probability Densities And Regression Curves written by Nadaraya and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-12-31 with Mathematics categories.
' this book is a useful and significant addition on the lively topic of nonparametric density and regression curve estimation.' Royal Statistical Society, 154, 1991
Nonparametric Estimation Of Probability Densities And Regression Curves
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Author : Nadaraya
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Nonparametric Estimation Of Probability Densities And Regression Curves written by Nadaraya 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 2012-12-06 with Mathematics categories.
'Et moi ..., si. j'avail su comment en revenir. One service mathematics has rendered!be human race. It has put common sense back jc n'y scrais point a1U: where it belongs, on the topmost sbelf next Jules Verne to \be dusty canister labelled 'discarded non- TIle series is divergent; therefore we may be sense'. able to do something with it Eric T. Bell O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics .. .'; 'One service logic bas rendered com puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.
Nonparametric Estimation Of Probability Densities And Regression Curves
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Author : 3Island Press
language : en
Publisher:
Release Date : 1988-12-31
Nonparametric Estimation Of Probability Densities And Regression Curves written by 3Island Press and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-12-31 with categories.
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.
Missing And Modified Data In Nonparametric Estimation
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Author : Sam Efromovich
language : en
Publisher: CRC Press
Release Date : 2018-03-12
Missing And Modified Data In Nonparametric Estimation written by Sam Efromovich and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-12 with Mathematics categories.
This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. All basic types of missing at random and not at random, biasing, truncation, censoring, and measurement errors are discussed, and their treatment is explained. Ten chapters of the book cover basic cases of direct data, biased data, nondestructive and destructive missing, survival data modified by truncation and censoring, missing survival data, stationary and nonstationary time series and processes, and ill-posed modifications. The coverage is suitable for self-study or a one-semester course for graduate students with a prerequisite of a standard course in introductory probability. Exercises of various levels of difficulty will be helpful for the instructor and self-study. The book is primarily about practically important small samples. It explains when consistent estimation is possible, and why in some cases missing data should be ignored and why others must be considered. If missing or data modification makes consistent estimation impossible, then the author explains what type of action is needed to restore the lost information. The book contains more than a hundred figures with simulated data that explain virtually every setting, claim, and development. The companion R software package allows the reader to verify, reproduce and modify every simulation and used estimators. This makes the material fully transparent and allows one to study it interactively. Sam Efromovich is the Endowed Professor of Mathematical Sciences and the Head of the Actuarial Program at the University of Texas at Dallas. He is well known for his work on the theory and application of nonparametric curve estimation and is the author of Nonparametric Curve Estimation: Methods, Theory, and Applications. Professor Sam Efromovich is a Fellow of the Institute of Mathematical Statistics and the American Statistical Association.
Nonparametric Functional Estimation And Related Topics
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Author : G.G Roussas
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Nonparametric Functional Estimation And Related Topics written by G.G Roussas 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 2012-12-06 with Mathematics categories.
About three years ago, an idea was discussed among some colleagues in the Division of Statistics at the University of California, Davis, as to the possibility of holding an international conference, focusing exclusively on nonparametric curve estimation. The fruition of this idea came about with the enthusiastic support of this project by Luc Devroye of McGill University, Canada, and Peter Robinson of the London School of Economics, UK. The response of colleagues, contacted to ascertain interest in participation in such a conference, was gratifying and made the effort involved worthwhile. Devroye and Robinson, together with this editor and George Metakides of the University of Patras, Greece and of the European Economic Communities, Brussels, formed the International Organizing Committee for a two week long Advanced Study Institute (ASI) sponsored by the Scientific Affairs Division of the North Atlantic Treaty Organization (NATO). The ASI was held on the Greek Island of Spetses between July 29 and August 10, 1990. Nonparametric functional estimation is a central topic in statistics, with applications in numerous substantive fields in mathematics, natural and social sciences, engineering and medicine. While there has been interest in nonparametric functional estimation for many years, this has grown of late, owing to increasing availability of large data sets and the ability to process them by means of improved computing facilities, along with the ability to display the results by means of sophisticated graphical procedures.
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.
Stochastic Curve Estimation
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Author : Murray Rosenblatt
language : en
Publisher: IMS
Release Date : 1991
Stochastic Curve Estimation written by Murray Rosenblatt and has been published by IMS this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Curve fitting categories.
Model Free Curve Estimation
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Author : Michael E. Tarter
language : en
Publisher: CRC Press
Release Date : 1993-12-16
Model Free Curve Estimation written by Michael E. Tarter and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-12-16 with Mathematics categories.
Model-Free Curve Estimation details the Fourier series approach to density estimation and explores how model-free technology can be expanded to deal with other statistical curves, such as survival and regression functions. It also describes the implementation of some curves for exploratory data analysis, including a specialized curve for detecting and analyzing hidden subpopulations in data and a family of curves useful for finding the best transformation and model to use in a statistical analysis.
Multivariate Density Estimation
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Author : David W. Scott
language : en
Publisher: John Wiley & Sons
Release Date : 2015-03-12
Multivariate Density Estimation written by David W. Scott and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-12 with Mathematics categories.
Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methods Featuring a thoroughly revised presentation, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition maintains an intuitive approach to the underlying methodology and supporting theory of density estimation. Including new material and updated research in each chapter, the Second Edition presents additional clarification of theoretical opportunities, new algorithms, and up-to-date coverage of the unique challenges presented in the field of data analysis. The new edition focuses on the various density estimation techniques and methods that can be used in the field of big data. Defining optimal nonparametric estimators, the Second Edition demonstrates the density estimation tools to use when dealing with various multivariate structures in univariate, bivariate, trivariate, and quadrivariate data analysis. Continuing to illustrate the major concepts in the context of the classical histogram, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition also features: Over 150 updated figures to clarify theoretical results and to show analyses of real data sets An updated presentation of graphic visualization using computer software such as R A clear discussion of selections of important research during the past decade, including mixture estimation, robust parametric modeling algorithms, and clustering More than 130 problems to help readers reinforce the main concepts and ideas presented Boxed theorems and results allowing easy identification of crucial ideas Figures in color in the digital versions of the book A website with related data sets Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition is an ideal reference for theoretical and applied statisticians, practicing engineers, as well as readers interested in the theoretical aspects of nonparametric estimation and the application of these methods to multivariate data. The Second Edition is also useful as a textbook for introductory courses in kernel statistics, smoothing, advanced computational statistics, and general forms of statistical distributions.