@article{Arendarczyk_J. Kozubowski_K. Panorska_2023, title={A Computational Approach to Confidence Intervals and Testing for Generalized Pareto Index Using the Greenwood Statistic}, volume={21}, url={https://revstat.ine.pt/index.php/REVSTAT/article/view/357}, DOI={10.57805/revstat.v21i3.357}, abstractNote={<p>The generalized Pareto distributions (GPDs) play an important role in the statistics of extremes. We point various problems with the likelihood-based inference for the index parameter α of the GPDs, and develop alternative testing strategies, which do not require parameter estimation. Our test statistic is the Greenwood statistic, which probability distribution is stochastically increasing with respect to α within the GPDs. We compare the performance of our test to a test with maximum-to-sum ratio test statistic R<sub>n</sub>. New results on the properties of the Rn are also presented, as well as recommendations for calculating the p-values and illustrative data examples.</p>}, number={3}, journal={REVSTAT-Statistical Journal}, author={Arendarczyk , Marek and J. Kozubowski , Tomasz and K. Panorska , Anna}, year={2023}, month={Jul.}, pages={367–388} }