Bayesian likelihood methods for estimating the end point of a distribution
We consider maximum likelihood methods for estimating the end point of a distribution. The likelihood function is modified by a prior distribution that is imposed on the location parameter. The prior is explicit and meaningful, and has a general form that adapts itself to different settings. Results on convergence rates and limiting distributions are given. In particular, it is shown that the limiting distribution is non-normal in non-regular cases. Parametric bootstrap techniques are suggested...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of the Royal Statistical Society Series B|
|01_Hall_Bayesian_likelihood_methods_2005.pdf||146.83 kB||Adobe PDF||Request a copy|
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