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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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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 represent a pair of stochastic processes that are jointly wide sense stationary with covariance functions and and cross-covariance function . Then the cross spectrum is defined as the Fourier transform of [1]
The cross-spectrum has representations as a decomposition into (i) its real part (co-spectrum) and its imaginary part (quadrature spectrum)
and (ii) in polar coordinates
Here, the amplitude spectrum is given by
and the phase spectrum given by
Squared coherency spectrum
The squared coherency spectrum is given by
which expresses the amplitude spectrum in dimensionless units.
See also
References
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