Inflation-restriction exact sequence: Difference between revisions

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General n, cite Koch
 
cite Gille & Szamuely (2006)
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{{Technical|date=April 2011}}
In [[time series analysis]], the '''cross-spectrum''' is used as part of a [[frequency domain]] analysis of the [[cross correlation]] or [[cross covariance]] between two time series.
 
== Definition ==
Let <math>(X_t,Y_t)</math> represent a pair of [[stochastic process]]es that are jointly [[wide sense stationary]] with covariance functions <math>\gamma_{xx}</math> and <math>\gamma_{yy}</math> and [[Cross-correlation#Time_series_analysis|cross-covariance function]] <math>\gamma_{xy}</math>. Then the cross spectrum <math>\Gamma_{xy}</math> is defined as the [[Fourier transform]] of <math>\gamma_{xy}</math> <ref>{{Cite book
| publisher = Cambridge Univ Pr
| isbn = 0-521-01230-9
| last = von Storch
| first = H.
| coauthors = F. W Zwiers
| title = Statistical analysis in climate research
| year = 2001
}}</ref>
 
: <math>
\Gamma_{xy}(f)= \mathcal{F}\{\gamma_{xy}\}(f) = \sum_{\tau=-\infty}^\infty \,\gamma_{xy}(\tau) \,e^{-2\,\pi\,i\,\tau\,f} .
</math>
 
The cross-spectrum has representations as a decomposition into (i) its real part (co-spectrum) and its imaginary part (quadrature spectrum)
: <math>
\Gamma_{xy}(f)= \Lambda_{xy}(f) + i \Psi_{xy}(f) ,
</math>
 
and (ii) in polar coordinates
: <math>
\Gamma_{xy}(f)= A_{xy}(f)  \,e^{i \phi_{xy}(f) } .
</math>
Here, the amplitude spectrum <math>A_{xy}</math> is given by
: <math>A_{xy}(f)= (\Lambda_{xy}(f)^2 + \Psi_{xy}(f)^2)^\frac{1}{2} ,</math>
and the phase spectrum <math>\Phi_{xy}</math> given by
: <math>\begin{cases}
  \tan^{-1} (  \Psi_{xy}(f) / \Lambda_{xy}(f)  )    & \text{if } \Psi_{xy}(f) \ne 0 \wedge \Lambda_{xy}(f) \ne 0 \\
  0    & \text{if } \Psi_{xy}(f) = 0 \text{ and } \Lambda_{xy}(f) > 0 \\
  \pm \pi & \text{if } \Psi_{xy}(f) = 0 \text{ and } \Lambda_{xy}(f) < 0 \\
  \pi/2 & \text{if } \Psi_{xy}(f) > 0 \text{ and } \Lambda_{xy}(f) = 0 \\
  -\pi/2 & \text{if } \Psi_{xy}(f) < 0 \text{ and } \Lambda_{xy}(f) = 0 \\
\end{cases}</math>
 
== Squared coherency spectrum ==
The squared [[Coherence (signal processing)|coherency spectrum]] is given by
: <math>
\kappa_{xy}(f)= \frac{A_{xy}^2}{ \Gamma_{xx}(f) \Gamma_{yy}(f)} ,
</math>
 
which expresses the amplitude spectrum in dimensionless units.
 
==See also==
* [[Cross-correlation#Time_series_analysis|Cross-correlation]]
* [[Spectral_density#Power_spectral_density|Power spectrum]]
* [[Scaled Correlation]]
 
==References==
<references/>
 
[[Category:Frequency domain analysis]]
[[Category:Multivariate time series analysis]]

Revision as of 22:08, 31 October 2012

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Also visit my web site ... hostgator1centcoupon.info In time series analysis, the cross-spectrum is used as part of a frequency domain analysis of the cross correlation or cross covariance between two time series.

Definition

Let (Xt,Yt) represent a pair of stochastic processes that are jointly wide sense stationary with covariance functions γxx and γyy and cross-covariance function γxy. Then the cross spectrum Γxy is defined as the Fourier transform of γxy [1]

Γxy(f)={γxy}(f)=τ=γxy(τ)e2πiτf.

The cross-spectrum has representations as a decomposition into (i) its real part (co-spectrum) and its imaginary part (quadrature spectrum)

Γxy(f)=Λxy(f)+iΨxy(f),

and (ii) in polar coordinates

Γxy(f)=Axy(f)eiϕxy(f).

Here, the amplitude spectrum Axy is given by

Axy(f)=(Λxy(f)2+Ψxy(f)2)12,

and the phase spectrum Φxy given by

{tan1(Ψxy(f)/Λxy(f))if Ψxy(f)0Λxy(f)00if Ψxy(f)=0 and Λxy(f)>0±πif Ψxy(f)=0 and Λxy(f)<0π/2if Ψxy(f)>0 and Λxy(f)=0π/2if Ψxy(f)<0 and Λxy(f)=0

Squared coherency spectrum

The squared coherency spectrum is given by

κxy(f)=Axy2Γxx(f)Γyy(f),

which expresses the amplitude spectrum in dimensionless units.

See also

References

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