Editing Spectral density (section)

== Estimation ==
{{main|Spectral density estimation}}

The goal of spectral density estimation is to [[estimation theory|estimate]] the spectral density of a [[random signal]] from a sequence of time samples. Depending on what is known about the signal, estimation techniques can involve [[parametric statistics|parametric]] or [[non-parametric statistics|non-parametric]] approaches, and may be based on time-domain or frequency-domain analysis. For example, a common parametric technique involves fitting the observations to an [[autoregressive model]]. A common non-parametric technique is the [[periodogram]].

The spectral density is usually estimated using [[Fourier transform]] methods (such as the [[Welch method]]), but other techniques such as the [[Maximum entropy spectral estimation|maximum entropy]] method can also be used.