Efektywność predykcji zmiennych zakłócających
Abstract
The author Investigates the efficiency of prediction of
noise variables in two cases, namely when these variables are
generated by causal models and by autoregressive models. In the
first case as the values of (random) explanatory variables in
the horizon of prediction are not known, it is assumed that
their extrapolated values are used instead. It is proved that
the efficiency of such prediction is always smaller than the
efficiency when autoregressive models are used.
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