(i) assuming that there is a true model;
(ii)
evaluating the efficiency of
the estimation as if the postulated model is true.
In this talk, we propose a new approach to empirical time series
modeling,
based on some foot-unbinding ideas. By liberating ourselves from the dictatorship of one-step-ahead
prediction errors, I shall illustrate, with
simulations and real data, the many benefits of the liberation.
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