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    Robust fitting of a Weibull model with optional censoring

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    Author
    Yang, Jingjing
    Scott, David W.
    Date
    2013
    Citation
    Yang, Jingjing and Scott, David W.. "Robust fitting of a Weibull model with optional censoring." Computational Statistics & Data Analysis, 67, (2013) 149-161. http://dx.doi.org/10.1016/j.csda.2013.05.009.
    Published Version
    http://dx.doi.org/10.1016/j.csda.2013.05.009
    Abstract
    The Weibull family is widely used to model failure data, or lifetime data, although the classical two-parameter Weibull distribution is limited to positive data and monotone failure rate. The parameters of the Weibull model are commonly obtained by maximum likelihood estimation; however, it is well-known that this estimator is not robust when dealing with contaminated data. A new robust procedure is introduced to fit a Weibull model by using L2 distance, i.e. integrated square distance, of the Weibull probability density function. The Weibull model is augmented with a weight parameter to robustly deal with contaminated data. Results comparing a maximum likelihood estimator with an L2 estimator are given in this article, based on both simulated and real data sets. It is shown that this new L2 parametric estimation method is more robust and does a better job than maximum likelihood in the newly proposed Weibull model when data are contaminated. The same preference for L2 distance criterion and the new Weibull model also happens for right-censored data with contamination.
    Keyword
    Weibull distribution; L2 distance; robust estimator; maximum likelihood; right-censored data; More... contamination Less...
    Type
    Journal article
    Citable link to this page
    http://hdl.handle.net/1911/78751
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    • Faculty Publications [2827]
    • Statistics Publications [81]

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    Managed by the Digital Scholarship Services at Fondren Library, Rice University
    Physical Address: 6100 Main Street, Houston, Texas 77005
    Mailing Address: MS-44, P.O.BOX 1892, Houston, Texas 77251-1892