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Maximum Likelihood Estimation and Diagnostics for Stable Distributions

In: Lévy Processes

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  • John P. Nolan

    (American University, Department of Mathematics and Statistics)

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.

Suggested Citation

  • John P. Nolan, 2001. "Maximum Likelihood Estimation and Diagnostics for Stable Distributions," Springer Books, in: Ole E. Barndorff-Nielsen & Sidney I. Resnick & Thomas Mikosch (ed.), Lévy Processes, pages 379-400, Springer.
  • Handle: RePEc:spr:sprchp:978-1-4612-0197-7_17
    DOI: 10.1007/978-1-4612-0197-7_17
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