Publication details


Kernel Smoothing in MATLAB: Theory and Practice of Kernel Smoothing

Basic information
Original title:Kernel Smoothing in MATLAB: Theory and Practice of Kernel Smoothing
Authors:Ivanka Horová, Jan Koláček, Jiří Zelinka
Further information
Citation:HOROVÁ, Ivanka, Jan KOLÁČEK a Jiří ZELINKA. Kernel Smoothing in MATLAB: Theory and Practice of Kernel Smoothing. Singapore: World Scientific Publishing Co. Pte. Ltd., 2012. 244 s. ISBN 978-981-4405-48-5.Export BibTeX
author = {Horová, Ivanka and Koláček, Jan and Zelinka, Jiří},
address = {Singapore},
keywords = {kernel smoothing; Matlab},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Singapore},
isbn = {978-981-4405-48-5},
publisher = {World Scientific Publishing Co. Pte. Ltd.},
title = {Kernel Smoothing in MATLAB: Theory and Practice of Kernel Smoothing},
url = {},
year = {2012}
Original language:English
Field:General mathematics
WWW:link to a new window
Keywords:kernel smoothing; Matlab

Methods of kernel estimates represent one of the most effective nonparametric smoothing techniques. These methods are simple to understand and they possess very good statistical properties. The book provides a brief comprehensive overview of statistical theory and moreover, the emphasis is given to implementation of presented methods in Matlab. All created programs are included into a special toolbox which is an integral part of the book. This toolbox contains many Matlab scripts useful for kernel smoothing of density, cumulative distribution function, regression function, hazard function, indices of quality and bivariate density. Especially, methods for a choice of the optimal bandwidth and a special procedure for simultaneous choice of the bandwidth, the kernel and its order are implemented. The toolbox is divided into six parts according to chapters of the book. All scripts are included in a user interface and it is easy to manipulate with this interface. Each chapter of the book contains a detailed help for the related part of the toolbox, too. The book is intended for newcomers to the field of smoothing techniques and would be also appropriate for a wide audience: students and researches from both the statistical science and interface disciplines.

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