Density Estimation

In probability and statistics, density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density function is thought of as the density according to which a large population is distributed; the data are usually thought of as a random sample from that population.

A variety of approaches to density estimation are used, including Parzen windows and a range of data clustering techniques, including vector quantization. The most basic form of density estimation is a rescaled histogram.

Read more about Density EstimationExample of Density Estimation

Other articles related to "density estimation":

Information Bottleneck Method - Gaussian Information Bottleneck - Density Estimation
... Since the bottleneck method is framed in probabilistic rather than statistical terms, we first need to estimate the underlying probability density at the sample points ... This is a well known problem with a number of solutions described by Silverman in ...
Fractal Flame - Density Estimation
... This problem can be solved with adaptive density estimation to increase image quality while keeping render times to a minimum ... Not all Flame implementations use density estimation ...
Example of Density Estimation - Script For Example
... The following commands of the R programming language will create the figures shown above ... These commands can be entered at the command prompt by using cut and paste ...

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    A higher class, in the estimation and love of this city- building, market-going race of mankind, are the poets, who, from the intellectual kingdom, feed the thought and imagination with ideas and pictures which raise men out of the world of corn and money, and console them for the short-comings of the day, and the meanness of labor and traffic.
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