Efficient Estimation for the Stable Laws

Andrey Feuerverger and Philip McDunnough
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Andrey Feuerverger: University of Toronto
Philip McDunnough: University of Toronto

A chapter in Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface, 1981, pp 49-55 from Springer

Abstract: Abstract This paper is concerned with Fourier procedures in inference which admit arbitrarily high asymptotic efficiency. The problem of estimation for the stable laws is treated by two different approaches. The first involves FFT inversion of the characteristic function. A detailed discussion is given of truncation and discretization effects with reference to the special structure of the stable densities. Some further results are give also concerning a second approach based on the empirical characteristic function (ecf). Finally we sketch an application of this method to testing for independence, and also present a stationary version of the ecf.

Keywords: Fourier transform; empirical characteristic function; stable laws; efficient estimation; stationarity (search for similar items in EconPapers)
Date: 1981
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4613-9464-8_9

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DOI: 10.1007/978-1-4613-9464-8_9

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