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:
algorithic approaches
wavelets and nonlinear smoothers
graphical methods and data mining
biostatistics and bioinformatics
bagging and boosting
support vector machines
resampling methods
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