1 Theory.- 2 RKHS AND STOCHASTIC PROCESSES.- 3 Nonparametric Curve Estimation.- 4 Measures And Random Measures.- 5 Miscellaneous Applications.- 6 Computational Aspects.- 7 A Collection of Examples.- to Sobolev spaces.- A.l Schwartz-distributions or generalized functions.- A.1.1 …
Hilbertian kernels and spline functions
by Atteia, Marc
fromStudies in computational mathematics
Hilbertian kernels and spline functions
by Atteia, Marc
fromStudies in computational mathematics
Hilbertian kernels and spline functions
by Atteia, Marc
fromStudies in computational mathematics
This book describes computational problems related to kernel density estimation (KDE) - one of the most important and widely used data smoothing techniques. A very detailed description of novel FFT-based algorithms for both KDE computations and bandwidth selection are presented.…
This book describes computational problems related to kernel density estimation (KDE)? one of the most important and widely used data smoothing techniques. A very detailed description of novel FFT-based algorithms for both KDE computations and bandwidth selection are presented. …
Density estimation -- Nonparametric regression -- Trend estimation -- Semiparametric regression -- Surface estimation
Kernel Smoothing explores both the theory and methods of kernel smoothing as well as introducing the fundamental methods and principles of related topics in parametric statistical inference. It addresses polynomials, with uncorrelated or i.i.d.
Kernel smoothing is a flexible nonparametric curve estimation method that is applicable when parametric descriptions of the data are not sufficiently adequate. This book explores theory and methods of kernel smoothing in a variety of contexts, considering independent and correla…
Comprehensive theoretical overview of kernel smoothing methods with motivating examples Kernel smoothing is a flexible nonparametric curve estimation method that is applicable when parametric descriptions of the data are not sufficiently adequate. This book explores theory and m…
Comprehensive theoretical overview of kernel smoothing methods with motivating examples Kernel smoothing is a flexible nonparametric curve estimation method that is applicable when parametric descriptions of the data are not sufficiently adequate. This book explores theory and m…
