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MSE of the best linear predictor in nonorthogonal models. (English) Zbl 1198.62120
Summary: The problem of computing the mean squared error (MSE) of the best linear predictor (BLP) in a finite discrete spectrum with an additive white noise model (FDSWNMs) for an observed time series is considered. This is done under the assumption that the corresponding vectors in models with finite observations of this time series are not orthogonal.
62M20 Inference from stochastic processes and prediction
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
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