Smoothing problem (stochastic processes): Difference between revisions

Revision as of 06:13, 28 November 2017

Revision as of 02:36, 9 May 2018

Line 1:

{{technical|date=November 2017}}

The '''Smoothing problem''' (not to be confused with [[smoothing]] in signal[[statistics]], [[image processing]] and other contexts) refers to [[Recursive Bayesian estimation]] also known as [[Bayes filter]] is the problem of [[density estimation|estimating]] an unknown [[probability density function]] recursively over time using incremental incoming measurements. It is one of the main problems defined by [[Norbert Wiener]]

<ref name="wiener-report">1942, ''Extrapolation, Interpolation and Smoothing of Stationary Time Series''. A war-time classified report nicknamed "the yellow peril" because of the color of the cover and the difficulty of the subject. Published postwar 1949 [[MIT Press]]. http://www.isss.org/lumwiener.htm])</ref>

.<ref name="wiener-book">Wiener, Norbert (1949). Extrapolation, Interpolation, and Smoothing of Stationary Time Series. New York: Wiley. {{ISBN|0-262-73005-7}}.</ref>