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Histogram Binwidth Optimization 1.0
File ID: 78809






Histogram Binwidth Optimization 1.0
Download Histogram Binwidth Optimization 1.0http://www.mathworks.comReport Error Link
License: Freeware
File Size: 10.0 KB
Downloads: 9
Submit Rating:
Histogram Binwidth Optimization 1.0 Description
Description: function [optN, C, N] = sshist(x,N)
[optN, C, N] = sshist(x,N)

Function `sshist' returns the optimal number of bins in a histogram
used for density estimation.
Optimization principle is to minimize expected L2 loss function between
the histogram and an unknown underlying density function.
An assumption made is merely that samples are drawn from the density
independently each other.

The optimal binwidth D* is obtained as a minimizer of the formula,
(2K-V) / D^2,
where K and V are mean and variance of sample counts across bins with width D.
Optimal number of bins is given as (max(x) - min(x)) / D*.

For more information, visit
http://2000.jukuin.keio.ac.jp/shimazaki/res/histogram.html

Original paper:
Hideaki Shimazaki and Shigeru Shinomoto
A method for selecting the bin size of a time histogram
Neural Computation 19(6), 1503-1527, 2007
http://dx.doi.org/10.1162/neco.2007.19.6.1503

Example usage:
optN = sshist(x); hist(x,optN);

Input argument
x: Sample data vector.
N (optinal):
A vector that specifies the number of bins to be examined.
The optimal number of bins is selected from the elements of N.
Default value is N = 2:50.
* Do not search binwidths smaller than a sampling resolution of data.

License: Freeware

Related: unknown, and an, shigeru, assumption, bins, 3d 250, sshistx, sshistxn, variance, drawn, between the, bin size, examined, assumption made, are mean, maxx, 2kv d2, 250 do, optimal number

O/S:BSD, Linux, Solaris, Mac OS X

File Size: 10.0 KB

Downloads: 9



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