If x(•) is a time series which may be written as $x(t) = s(t) + n(t)$ where t is an integer, s(•) an autoregressive signal of order q and n(•) white noise, then the model has $q + 2$ parameters. These are (i) the q autoregressive parameters (ii) the residual variance of the autoregressive scheme and (iii) the variance of the white noise. A method is proposed to estimate the $q + 2$ parameters. This method is based on analogies with regression theory and in the case of a normal series yields strongly consistent efficient estimators.
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A 1974 study studied this question.