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Moment estimators for the two-parameter M-Wright distribution

  • Dexter Cahoy

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    A formal parameter estimation procedure for the two-parameter M-Wright distribution is proposed. This procedure is necessary to make the model useful for real-world applications. Note that its generalization of the Gaussian density makes the M-Wright distribution appealing to practitioners. Closed-form estimators are also derived from the moments of the log-transformed M-Wright distributed random variable, and are shown to be asymptotically normal. Tests using simulated data indicated favorable results for our estimation procedure. Copyright Springer-Verlag 2012

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    File URL: http://hdl.handle.net/10.1007/s00180-011-0269-x
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    Article provided by Springer in its journal Computational Statistics.

    Volume (Year): 27 (2012)
    Issue (Month): 3 (September)
    Pages: 487-497

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    Handle: RePEc:spr:compst:v:27:y:2012:i:3:p:487-497
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    1. Guido Germano & Mauro Politi & Enrico Scalas & Ren\'e L. Schilling, 2008. "Stochastic calculus for uncoupled continuous-time random walks," Papers 0802.3769, arXiv.org, revised Jan 2009.
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