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

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  • Bhansali, R. J.

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.

Suggested Citation

  • Bhansali, R. J., 1983. "The inverse partial correlation function of a time series and its applications," Journal of Multivariate Analysis, Elsevier, vol. 13(2), pages 310-327, June.
    • Handle: RePEc:eee:jmvana:v:13:y:1983:i:2:p:310-327
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    Cited by:

    1. Rahiala, Markku, . "On the Identification and Estimation of Multiple Input Transfer Function Models with Autocorrelated Errors," ETLA A, The Research Institute of the Finnish Economy, number 8.

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