Kernel density estimation and Talk:Mayer Amschel Rothschild: Difference between pages

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Why is his middle name commonly spelled as Amschel, when it is actually Anschel? The inscriptions on his children's graves spell it in Hebrew as אנשיל.
The '''Parzen window''' method is a way of estimating the [[probability density function]] of a [[random variable]]. As an illustration, given some data about a ''sample'' of a population, the Parzen window method makes it possible to [[extrapolation|extrapolate]] the data to the entire population.
Many of the children have Mayer in their names, so it doesn't seem logical that this is a given name. Could it be the family name in Hebrew, to which the Rothschild name was appended?
 
If ''x''<sub>1</sub>, ''x''<sub>2</sub>, ..., ''x''<sub>N</sub> is a [[statistical sample|sample]] of a random variable, then the Parzen window approximation of its probability density function is
:<math>\rho(x)=\frac{1}{N}\sum_{i=1}^N W(x-x_i)</math>
where ''W'' is some kernel. Quite often ''W'' is taken to be a [[Gaussian function]] with mean zero and [[variance]] &sigma;<sup>2</sup>:
:<math>W(x) = {1 \over \sigma\sqrt{2\pi} }\,e^{-{x^2 / 2\sigma^2}}.</math>
 
[[Image: Parzen_window_illustration.png|frame|center|The Parzen window density estimate &rho;(''x'') is in blue; the Gaussians which add up to &rho;(''x'') are in red. Six sample points were considered. The variance of the Gaussians was set to 0.5. Note that where the points are denser, the density estimate has higher values.</sup>]]
 
==See also==
*[[Density estimation]].
 
==References==
* Parzen E. (1962). ''On estimation of a probability density function and mode'', Ann. Math. Stat. '''33''', pp. 1065-1076.
 
* Duda, R. and Hart, P. (1973). ''Pattern Classification and Scene Analysis''. John Wiley & Sons. ISBN 0471223611.
 
==External links==
*[http://mathworld.wolfram.com/ParzenWindow.html Parzen Window -- from MathWorld]
[[Category:Probability and statistics]]