Издательство: | Книга по требованию |
Дата выхода: | июль 2011 |
ISBN: | 978-6-1318-1368-9 |
Объём: | 72 страниц |
Масса: | 129 г |
Размеры(В x Ш x Т), см: | 23 x 16 x 1 |
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.
Данное издание не является оригинальным. Книга печатается по технологии принт-он-деманд после получения заказа.