Abstract
A linear process is generated by applying a linear filter to independent, identically distributed random variables. Only the modulus of the frequency response function can be estimated if only the linear process is observed and if the independent identically distributed random variables are Gaussian. In this case a number of distinct but related problems coalesce and the usual discussion of these problems assumes, for example, in the case of a moving average that the zeros of the polynomial given by the filter have modulus greater than one. However, if the independent identically distributed random variables are non-Gaussian, these problems become distinct and one can estimate the transfer function under appropriate conditions except for a possible linear phase shift by using higher-order spectral estimates.
Received 5 December 1978; revision received 23 February 1979.
Research partially supported by the Office of Naval Research Contract N00014-75-C-0428.
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Davis, R.A., Lii, KS., Politis, D.N. (2011). Linear Processes and Bispectra. In: Davis, R., Lii, KS., Politis, D. (eds) Selected Works of Murray Rosenblatt. Selected Works in Probability and Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8339-8_30
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DOI: https://doi.org/10.1007/978-1-4419-8339-8_30
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