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In a previous paper, a frequency estimator using only three Fourier coefficients was introduced, which has asymptotic variance of order. In this correspondence, a similar technique of Rife and Vincent is shown to have asymptotic variance of larger order. A new estimator is introduced that has asymptotic variance less than 1.65 times the CRLB.

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This paper is concerned with autoregressive models in which the coefficients are assumed to be not constant but subject to random perturbations so that we are considering a class of random coefficient autoregressive models. By means of a two stage regression procedure estimates of the unknown parameters of these models are obtained. The estimates are shown to be strongly consistent and to satisfy a central limit theorem. A number of Monte Carlo experiments was carried out to illustrate the estimation procedure and their results are reported.