Bibliothèque de L'IMIST/CNRST

The advent of high-speed, affordable computers in the last two decades has given a new boost to the nonparametric way of thinking. Classical nonparametric procedures, such as function smoothing, suddenly lost their abstract flavour as they became practically implementable. In addition, many previously unthinkable possibilities became mainstream; prime examples include the bootstrap and resampling methods, wavelets and nonlinear smoothers, graphical methods, data mining, bioinformatics, as well as the more recent algorithmic approaches such as bagging and boosting. This volume is a collection of short articles - most of which having a review component - describing the state-of-the art of Nonparametric Statistics at the beginning of a new millennium. Key features: and bull; algorithic approaches and bull; wavelets and nonlinear smoothers and bull; graphical methods and data mining and bull; biostatistics and bioinformatics and bull; bagging and boosting and bull; support vector machines and bull; resampling methods.

Includes bibliographical references and index.

Description based on print version record.