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Moment estimators for the two-parameter M-Wright distribution

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Abstract

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.

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Authors and Affiliations

  1. Program of Mathematics and Statistics, College of Engineering and Science, Louisiana Tech University, Ruston, LA, USA

    Dexter O. Cahoy

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  1. Dexter O. Cahoy
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Correspondence to Dexter O. Cahoy.

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Cahoy, D.O. Moment estimators for the two-parameter M-Wright distribution. Comput Stat 27, 487–497 (2012). https://doi.org/10.1007/s00180-011-0269-x

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  • DOI: https://doi.org/10.1007/s00180-011-0269-x

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