Maximum Likelihood Estimation and Diagnostics for Stable Distributions

John P. Nolan ()
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John P. Nolan: American University, Department of Mathematics and Statistics

A chapter in Lévy Processes, 2001, pp 379-400 from Springer

Abstract: Abstract A program for maximum likelihood estimation of general stable parameters is described. The Fisher information matrix is computed, making large sample estimation of stable parameters a practical tool. In addition, diagnostics are developed for assessing the stability of a data set. Applications to simulated data, stock price data, foreign exchange rate data, radar data, and ocean wave energy are presented.

Keywords: Stable Parameter; Stable Model; Heavy Tail; Fisher Information Matrix; Stable Distribution (search for similar items in EconPapers)
Date: 2001
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4612-0197-7_17

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DOI: 10.1007/978-1-4612-0197-7_17

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