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  • Theory & Methods: A Starship Estimation Method for the Generalized λ Distributions

    Author(s)
    King, Robert
    MacGillivray, H.
    Griffith University Author(s)
    King, Robert AR.
    Year published
    1999
    Metadata
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    Abstract
    A development of the ‘starship’ method (Owen, 1988), a computer intensive estimation method, is presented for two forms of generalized λ distributions (gλd). The method can be used for the full parameter space and is flexible, allowing choice of both the form of the generalized λ distribution and of the nature of fit required. Some examples of its use in fitting data and approximating distributions are given. Some simulation studies explore the sampling distribution of the parameter estimates produced by this method for selected values of the parameters and consider comparisons with two other methods, for one of the gλd ...
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    A development of the ‘starship’ method (Owen, 1988), a computer intensive estimation method, is presented for two forms of generalized λ distributions (gλd). The method can be used for the full parameter space and is flexible, allowing choice of both the form of the generalized λ distribution and of the nature of fit required. Some examples of its use in fitting data and approximating distributions are given. Some simulation studies explore the sampling distribution of the parameter estimates produced by this method for selected values of the parameters and consider comparisons with two other methods, for one of the gλd distributional forms, not previously so investigated. In the forms and parameter regions available to the other methods, it is demonstrated that the starship compares favourably. Although the differences between the methods, where available, tend to disappear with largersamples, the parameter coverage, flexibility and adaptability of the starship method make it attractive. However, the paper also demonstrates that care is needed when fitting and using such quantile‐defined distributional families that are rich in shape, but have complex properties.
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    Journal Title
    Australian and New Zealand Journal of Statistics
    Volume
    41
    Issue
    3
    DOI
    https://doi.org/10.1111/1467-842X.00089
    Subject
    Statistics
    Econometrics
    Publication URI
    http://hdl.handle.net/10072/122259
    Collection
    • Journal articles

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