Kernel Density Estimation (Paperback)

High Quality Content by WIKIPEDIA articles! In statistics, kernel density estimation (or Parzen window method, named after Emanuel Parzen) is a non- parametric way of estimating the probability density function of a random variable. As an illustration, given some data about a sample of a population, kernel density estimation makes it possible to extrapolate the data to the entire population. The Parzen window is also used in signal processing as a lag window, in such procedures as the Blackman-Tukey procedure. A histogram can be thought of as a collection of point samples from a kernel density estimate for which the kernel is a uniform box the width of the histogram bin.