View source for Spectral analysis of a stationary stochastic process

''spectral analysis of a time series''

The same as spectral decomposition of a [[Stationary stochastic process|stationary stochastic process]] (cf. [[Spectral decomposition of a random function|Spectral decomposition of a random function]]).

A set of statistical methods that enables one to estimate the value of the spectral density of a stationary stochastic process from the observed data of one (or several) realization(s) of this process (see [[#References|[1]]]–[[#References|[5]]]). See also [[Statistical problems in the theory of stochastic processes|Statistical problems in the theory of stochastic processes]]; [[Periodogram|Periodogram]]; [[Spectral density, estimator of the|Spectral density, estimator of the]]; [[Maximum-entropy spectral estimator|Maximum-entropy spectral estimator]]; [[Spectral estimator, parametric|Spectral estimator, parametric]].

====References====
<table><TR><TD valign="top">[1]</TD> <TD valign="top">  G.M. Jenkins,   D.G. Watts,   "Spectral analysis and its applications" , '''1–2''' , Holden-Day  (1968)</TD></TR><TR><TD valign="top">[2]</TD> <TD valign="top">  D.G. Childers (ed.) , ''Modern spectrum analysis'' , IEEE  (1978)</TD></TR><TR><TD valign="top">[3]</TD> <TD valign="top">  S.S. Haykin (ed.) , ''Nonlinear methods of spectral analysis'' , Springer  (1983)</TD></TR><TR><TD valign="top">[4]</TD> <TD valign="top">  S.M. Kay,   S.L. Marple,   "Spectrum analysis - A modern perspective" , ''Proc. IEEE'' , '''69''' :  11  (1981)  pp. 1380–1419  (Erratum: Vol. 70 (1982), 120; Comments: Vol. 71 (1983), 776–779; 1324–1325)</TD></TR><TR><TD valign="top">[5]</TD> <TD valign="top">  "Spectral estimation"  ''Proc. IEEE'' , '''70''' :  9  (1982)  ((Special Issue))</TD></TR><TR><TD valign="top">[6]</TD> <TD valign="top">  S.M. Kay,   "Modern spectral estimation" , Prentice-Hall  (1987)</TD></TR><TR><TD valign="top">[7]</TD> <TD valign="top">  S.L. Marple,   "Digital spectral analysis with applications" , Prentice-Hall  (1987)</TD></TR></table>