NonGaussian linear processes are considered. It is shown that the phase of the transfer function can be estimated under broad conditions. This is not true of Gaussian linear processes and in this sense Gaussian linear processes are atypical. The asymptotic behavior of a phase estimate is determined. The phase estimates make use of bispectral estimates. These ideas are applied to a problem of deconvolution which is effective even when the transfer function is not minimum phase. A number of computational illustrations are given.
"Deconvolution and Estimation of Transfer Function Phase and Coefficients for Nongaussian Linear Processes." Ann. Statist. 10 (4) 1195 - 1208, December, 1982. https://doi.org/10.1214/aos/1176345984