
- 522 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Recent Advances and Trends in Nonparametric Statistics
About this book
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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Information
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright page
- Preface
- 1: Algorithmic Approaches to Statistics
- 2: Functional Data Analysis
- 3: Nonparametric Model Building and Inference
- 4: Goodness of Fit
- 5: High-dimensional Data and Visualization
- 6: Nonparametric Regression
- 7: Topics in Nonparametrics
- 8: Nonparametrics in Finance and Risk Management
- 9: Bioinformatics and Biostatistics
- 10: Resampling and Subsampling
- 11: Time Series and Stochastic Processes
- 12: Wavelet and Multiresolution Methods
- Author Index