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Correlated Data
Covariance Matrix
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Linear Regression
Magnetohydrodyna...
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Regression with strongly correlated data
Regression with strongly correlated data,10.1016/j.jmva.2008.02.008,Journal of Multivariate Analysis,Christopher S. Jones,John M. Finn,Nicolas Hengart
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Regression with strongly correlated data
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Christopher S. Jones
,
John M. Finn
,
Nicolas Hengartner
This paper discusses
linear regression
of strongly
correlated data
that arises, for example, in magnetohydrodynamic equilibrium reconstructions. We have proved that, generically, the
covariance matrix
of the estimated regression parameters for fixed
sample size
goes to zero as the correlations become unity. That is, in this limit the estimated parameters are known with perfect accuracy. Simple examples are shown to illustrate this effect and the nature of the exceptional cases in which the covariance of the estimate does not go to zero.
Journal:
Journal of Multivariate Analysis  J MULTIVARIATE ANAL
, vol. 99, no. 9, pp. 21362153, 2008
DOI:
10.1016/j.jmva.2008.02.008
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Testing for Spatial Autocorrelation: The Regressors that Make the Power Disappear
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Citations: 1
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Federico Martellosio
Journal:
Econometric Reviews  ECONOM REV
, vol. 31, no. 2, pp. 215240, 2012