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自适应核密度估计matlab程序,matlab实现局部自适应核密度估计

自适应核密度估计代码

Locally Adaptive Kernel Density Estimation

First thing to do:

Run a tutorial code, tutorial.m

Documentation:

http://2000.jukuin.keio.ac.jp/shimazaki/res/kernel.html

see also sskernel for optimization of a fixed kernel bandwidth and sshist for histogram optimization.

% [y,t,optw,gs,C,confb95,yb] = ssvkernel(x,t,W)

%

% Function `ssvkernel' returns an optimized kernel density estimate

% using a Gauss kernel function with bandwidths locally adapted to the data.

%

% Examples:

% >> x = 0.5-0.5*log(rand(1,1e3)); t = linspace(0,3,500);

% >> [y,t,optw] = ssvkernel(x,t);

% This example produces a vector of kernel density estimates, y, at points

% specified in a vector t, using locally adaptive bandwidths, optw

% (a standard deviation of a normal density function).

%

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