The inverse partial correlation function of a time series and its applications

R. J. Bhansali

Journal of Multivariate Analysis, 1983, vol. 13, issue 2, 310-327

Abstract: The concept of the inverse correlation function of a stationary process was introduced by Cleveland (Technometrics 14 (1972), 277-293). The inverse partial correlation function of a stationary process may intuitively be thought of as the corresponding extension of the concept of the partial correlation function. A precise mathematical definition of this function is given. Its importance in describing the structure of a moving average of finite order h is discussed. Having observed X1,...,XT, the autoregressive method of estimating the inverse correlations is employed for constructing sample estimates of the inverse partial correlations. For the hth-order moving average process, the estimates beyond h are, as T --> [infinity], asymptotically independent normally distributed with 0 mean and variance T-1. Their use for estimating h and for testing hypotheses concerning h is examined.

Keywords: Inverse; covariance; function; inverse; correlation; function; partial; correlation; function; inverse; partial; correlation; function; autoregressive; spectral; estimate; moving; average; model (search for similar items in EconPapers)
Date: 1983
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