Limited distribution of sample partial autocorrelations: A matrix approach

Simon F. Ku

Stochastic Processes and their Applications, 1997, vol. 72, issue 1, 121-143

Abstract: We develop a technique for derivation of the asymptotic joint distribution of the sample partial autocorrelations of a process, given the corresponding distribution of sample autocorrelations. No assumption of asymptotic normality is needed. The underlying process need not be stationary. The technique is demonstrated through a detailed study of ARMA (1,1)-like processes, but is applicable to other models. The results extend those of Mills and Seneta (1989) for the AR(1)-like case. The study is motivated by the known relationships and properties, especially is the classical AR(p) case, of population and sample partial autocorrelations.

Keywords: Sample; autocorrelations; Sample; partial; autocorrelations; Autoregressive; moving-average; processes; Non-stationarity (search for similar items in EconPapers)
Date: 1997
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