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. This
book provides a concise and comprehensive overview of statistical
theory and in addition, emphasis is given to the implementation of
presented methods in Matlab. All created programs are included in 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.
Specifically, methods for choosing 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 the 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. This book is
intended for newcomers to the field of smoothing techniques and
would also be appropriate for a wide audience: advanced graduate,
PhD students and researchers from both the statistical science and
interface disciplines.
General
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