The Annals of Statistics

Deconvolution and Estimation of Transfer Function Phase and Coefficients for Nongaussian Linear Processes

K. S. Lii and M. Rosenblatt

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Abstract

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.

Article information

Source
Ann. Statist., Volume 10, Number 4 (1982), 1195-1208.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176345984

Digital Object Identifier
doi:10.1214/aos/1176345984

Mathematical Reviews number (MathSciNet)
MR673654

Zentralblatt MATH identifier
0512.62090

JSTOR
links.jstor.org

Subjects
Primary: 62M15: Spectral analysis
Secondary: 62G99: None of the above, but in this section

Keywords
Asymptotics bispectrum deconvolution linear process non-Gaussian phase

Citation

Lii, K. S.; Rosenblatt, M. Deconvolution and Estimation of Transfer Function Phase and Coefficients for Nongaussian Linear Processes. Ann. Statist. 10 (1982), no. 4, 1195--1208. doi:10.1214/aos/1176345984. https://projecteuclid.org/euclid.aos/1176345984


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