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: ac algorithic approaches ac wavelets and nonlinear smoothers ac graphical methods and data mining ac biostatistics and bioinformatics ac bagging and boosting ac support vector machines ac resampling methodsNonparametric Methods in Continuous-Time Finance: A Selective Review * Zongwu Cai * and Yongmiao Hongaquot; ... Much theoretical and empirical research is needed in this area, and we point out several aspects that deserve furtheranbsp;...
|Title||:||Recent Advances and Trends in Nonparametric Statistics|
|Author||:||M.G. Akritas, D.N. Politis|
|Publisher||:||Elsevier - 2003-10-31|