Fitting autoregression with regularly missed observations

The effect of regularly missed observations on the estimation of parameters of an autoregressive (AR) process is investigated by using the frequency domain method. For first order AR processes, numerical results are shown to see a behavior of variances of the estimate due to the missed observations. In some cases, we can positively utilize the concept of missed observations to decrease the variances if the number of observations is fixed but time instants at with the observations are made can be changed.