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Comparison of estimators of the Weibull Distribution

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  • Muhammad Akram

    ()
    (Monash University)

  • Aziz Hayat

    ()
    (Deakin University)

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    Abstract

    We compare the small sample performance (in terms of bias and root mean squared error) of L-moment estimator of 3-parameter Weibull distribution with Maximum likelihood Estimation (MLE), Moment Estimation (MoE), Least squared estimation (LSE), the Modified MLE (MMLE), Modified MoE (MMoE), and the Maximum Product of Spacing (MPS). Overall, the LM method has the tendency to perform well as it is almost always close to the best method of estimation. The ML performance is remarkable even in small sample of size n = 10 when the shape parameter β lies in [1.5, 4] range.

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    File URL: http://www.deakin.edu.au/buslaw/aef/workingpapers/fin-econometrics/2012_04.pdf
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    Bibliographic Info

    Paper provided by Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance in its series Financial Econometics Series with number 2012_04.

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    Length: 31
    Date of creation: 26 Mar 2012
    Date of revision:
    Handle: RePEc:dkn:ecomet:fe_2012_04

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    Related research

    Keywords: Weibull distribution; Order statistics; L-moment estimation; Maximum likelihood estimation; Methods of moments; Maximum Product of Spacing;

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    1. James Hammitt & Jin-Tan Liu, 2004. "Effects of Disease Type and Latency on the Value of Mortality Risk," Journal of Risk and Uncertainty, Springer, vol. 28(1), pages 73-95, January.
    2. Bartolucci, Alfred A. & Singh, Karan P. & Bartolucci, Anne D. & Bae, Sejong, 1999. "Applying medical survival data to estimate the three-parameter Weibull distribution by the method of probability-weighted moments," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 48(4), pages 385-392.
    3. Stelios H. Zanakis, 1979. "Extended Pattern Search with Transformations for the Three-Parameter Weibull MLE Problem," Management Science, INFORMS, vol. 25(11), pages 1149-1161, November.
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