Estimation and prediction based on k-record values from a generalized Pareto distribution
In this paper, the upper k-record values arising from a generalized Pareto distribution is considered. After computing the means, variances and covariances of the upper k-record values, the best linear unbiased estimators for the location and scale parameters of generalized Pareto distribution are obtained. The best linear unbiased predictor of future k-record value is also determined. The proposed method of estimation for the generalized Pareto distribution provides the extension of the convensional record values to the k-record values. Further, the occurrence of convensional record values are rare in practical situations, the proposed k-record values
are more applicable in real life situations. Finally, a real data set is considered to illustrate the proposed inference procedures developed in this paper.
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