Approximate studentization for Pareto distribution with application to censored data

The use of the Pareto distribution as a model for various socio-economic phenomena dates back to the late nineteenth century. Recently, it has also been recognized as a useful model for the analysis of lifetime data. In this paper, we apply the approximate studentization method to obtain inference for the scale parameter of the Pareto distribution, and also for the strong Pareto law. Moreover, we extend the method to construct prediction limits for thejth smallest future observation based on the firstk observed data.