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Author : Albertus Jacob Es
Publisher :
ISBN 13 :
Total Pages : 15 pages
Book Rating : 4.:/5 (685 download)
Download or read book Simple Kernel Estimators for Certain Nonparametric Deconvolution Problems written by Albertus Jacob Es and published by . This book was released on 1997 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Alexander Meister
Publisher : Springer Science & Business Media
ISBN 13 : 3540875573
Total Pages : 211 pages
Book Rating : 4.5/5 (48 download)
Download or read book Deconvolution Problems in Nonparametric Statistics written by Alexander Meister and published by Springer Science & Business Media. This book was released on 2009-12-24 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deconvolution problems occur in many ?elds of nonparametric statistics, for example, density estimation based on contaminated data, nonparametric - gression with errors-in-variables, image and signal deblurring. During the last two decades, those topics have received more and more attention. As appli- tions of deconvolution procedures concern many real-life problems in eco- metrics, biometrics, medical statistics, image reconstruction, one can realize an increasing number of applied statisticians who are interested in nonpa- metric deconvolution methods; on the other hand, some deep results from Fourier analysis, functional analysis, and probability theory are required to understand the construction of deconvolution techniques and their properties so that deconvolution is also particularly challenging for mathematicians. Thegeneraldeconvolutionprobleminstatisticscanbedescribedasfollows: Our goal is estimating a function f while any empirical access is restricted to some quantity h = f?G = f(x?y)dG(y), (1. 1) that is, the convolution of f and some probability distribution G. Therefore, f can be estimated from some observations only indirectly. The strategy is ˆ estimating h ?rst; this means producing an empirical version h of h and, then, ˆ applying a deconvolution procedure to h to estimate f. In the mathematical context, we have to invert the convolution operator with G where some reg- ˆ ularization is required to guarantee that h is contained in the invertibility ˆ domain of the convolution operator. The estimator h has to be chosen with respect to the speci?c statistical experiment.
Author : A. J. van Es
Publisher :
ISBN 13 :
Total Pages : 18 pages
Book Rating : 4.:/5 (249 download)
Download or read book Multi Bandwidth Kernel Estimators for Nonparametric Deconvolution Problems written by A. J. van Es and published by . This book was released on 1999 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : M.P. Wand
Publisher : CRC Press
ISBN 13 : 9780412552700
Total Pages : 230 pages
Book Rating : 4.5/5 (527 download)
Download or read book Kernel Smoothing written by M.P. Wand and published by CRC Press. This book was released on 1994-12-01 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 facilitated by the authors' focus on the simplest settings, namely density estimation and nonparametric regression. They pay particular attention to the problem of choosing the smoothing parameter of a kernel smoother, and also treat the multivariate case in detail. Kernal Smoothing is self-contained and assumes only a basic knowledge of statistics, calculus, and matrix algebra. It is an invaluable introduction to the main ideas of kernel estimation for students and researchers from other discipline and provides a comprehensive reference for those familiar with the topic.
Author : Artur Gramacki
Publisher : Springer
ISBN 13 : 3319716883
Total Pages : 197 pages
Book Rating : 4.3/5 (197 download)
Download or read book Nonparametric Kernel Density Estimation and Its Computational Aspects written by Artur Gramacki and published by Springer. This book was released on 2017-12-21 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes computational problems related to kernel density estimation (KDE) – one of the most important and widely used data smoothing techniques. A very detailed description of novel FFT-based algorithms for both KDE computations and bandwidth selection are presented. The theory of KDE appears to have matured and is now well developed and understood. However, there is not much progress observed in terms of performance improvements. This book is an attempt to remedy this. The book primarily addresses researchers and advanced graduate or postgraduate students who are interested in KDE and its computational aspects. The book contains both some background and much more sophisticated material, hence also more experienced researchers in the KDE area may find it interesting. The presented material is richly illustrated with many numerical examples using both artificial and real datasets. Also, a number of practical applications related to KDE are presented.
Author : Ming-Chung Liu
Publisher :
ISBN 13 :
Total Pages : 222 pages
Book Rating : 4.:/5 (174 download)
Download or read book Nonparametric Density Function Estimation and the Deconvolution Problem written by Ming-Chung Liu and published by . This book was released on 1987 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Robert David Murison
Publisher :
ISBN 13 :
Total Pages : 276 pages
Book Rating : 4.:/5 (222 download)
Download or read book Problems in Density Estimation for Independent and Dependent Data written by Robert David Murison and published by . This book was released on 1993 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Peter Malec
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (115 download)
Download or read book Nonparametric Kernel Density Estimation Near the Boundary written by Peter Malec and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : B. van Es
Publisher :
ISBN 13 :
Total Pages : 18 pages
Book Rating : 4.:/5 (192 download)
Download or read book Some Thoughts Ion the Asymptotics of the Deconvolution Kernel Density Estimator written by B. van Es and published by . This book was released on 2008 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Aren J. H. van Es (Physiologist, Netherlands)
Publisher :
ISBN 13 :
Total Pages : 25 pages
Book Rating : 4.:/5 (637 download)
Download or read book Convex Minorant Estimators of Distributions in Nonparametric Deconvolution Problems written by Aren J. H. van Es (Physiologist, Netherlands) and published by . This book was released on 1990 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Christian Wagner
Publisher :
ISBN 13 :
Total Pages : 170 pages
Book Rating : 4.:/5 (436 download)
Download or read book Deconvolution Problems in Density Estimation written by Christian Wagner and published by . This book was released on 2009 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ling Lan
Publisher :
ISBN 13 :
Total Pages : 212 pages
Book Rating : 4.:/5 (72 download)
Download or read book On the Nonparametric Estimation of the Overlapping Coefficient written by Ling Lan and published by . This book was released on 2005 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis investigated the properties and sampling behaviors of the nonparametric estimators of the overlapping coefficient (OVL) between two normal or Weibull distributions using three kernel density estimation techniques: naïve, Gaussian, and Epanechnikov kernel density estimators. Monte Carlo simulation was used to study the properties of the mean and variance of the OVL estimators. The bootstrap variance of the OVL was also estimated. Estimating the OVL with the naïve kernel estimator tended to underestimate the similarity between the two distributions. The bias increased as the true OVL increased. The Gaussian and the Epanechnikov kernel estimators were more reliable if the two distributions of interest were neither identical nor greatly dissimilar. The comparison of the three kernel estimators of the OVL was conducted using the relative bias and the ratio of the variances. The Gaussian and Epanechnikov kernel density estimators have advantages over the naïve kernel density estimator in both accuracy and efficiency.
Author : Michael H. Neumann
Publisher :
ISBN 13 :
Total Pages : 26 pages
Book Rating : 4.:/5 (632 download)
Download or read book On the Effect of Estimating the Error Density in Nonparametric Deconvolution written by Michael H. Neumann and published by . This book was released on 1995 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Albertus Jacob Es
Publisher :
ISBN 13 :
Total Pages : 22 pages
Book Rating : 4.:/5 (778 download)
Download or read book Asymptotic Normality of the Deconvolution Kernel Density Estimator Under the Vanishing Error Variance written by Albertus Jacob Es and published by . This book was released on 2009 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : A. J. van Es
Publisher :
ISBN 13 :
Total Pages : 158 pages
Book Rating : 4.3/5 (91 download)
Download or read book Aspects of Nonparametric Density Estimation written by A. J. van Es and published by . This book was released on 1991 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Bert van Es
Publisher :
ISBN 13 :
Total Pages : 13 pages
Book Rating : 4.:/5 (467 download)
Download or read book On the Integrated Squared Error of a Kernel Density Estimator in Non-smooth Cases written by Bert van Es and published by . This book was released on 1994 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "Let X1 ..., X[subscript n] be a random sample from a distribution on the real line with an unknown density f. We discuss the performance of the classical kernel density estimator of the density f. The properties of kernel estimators in cases where the density f to be estimated is sufficiently smooth are well known. Instead we focus on estimation problems where f is non-smooth, i.e. f is allowed to have a finite number of jumps or kinks. Thus the robustness properties of the kernel estimator against unfulfilled smoothness assumptions are illustrated. After a review of properties of the mean integrated squared error we present a central limit theorem for the integrated squared error. This theorem extends results of Bickel, Rosenblatt and Hall. Finally, the distance between the bandwidth minimizing the integrated squared error and the bandwidth which minimizes the mean integrated squared error is discussed."
![Download Applications of Nonparametric Kernel-type Density Estimators [microform] PDF Online Free](https://books.google.com/books/content/images/frontcover/5oQbAAAACAAJ?fife=w200-h370)
Author : Edit Gombay
Publisher : National Library of Canada
ISBN 13 : 9780315327450
Total Pages : 254 pages
Book Rating : 4.3/5 (274 download)
Download or read book Applications of Nonparametric Kernel-type Density Estimators [microform] written by Edit Gombay and published by National Library of Canada. This book was released on 1986 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt:
