Abstract
The paper examines the applicability of correlation analysis to identification of some classes of nonstationary processes. Consistency conditions are obtained for the time-dependent 1st order autoregressive (AR) process and for the polynomial AR model of an arbitrary order. These results are applied for stable AR estimation and for linear prediction on given classes of nonstationary processes.
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