Pires, Juliana F.; Cysneiros, Audrey H. M. A.; Cribari-Neto, Francisco Improved inference for the generalized Pareto distribution. (English) Zbl 1404.62020 Braz. J. Probab. Stat. 32, No. 1, 69-85 (2018). Summary: The generalized Pareto distribution is commonly used to model exceedances over a threshold. In this paper, we obtain adjustments to the generalized Pareto profile likelihood function using the likelihood function modifications proposed by O. Barndorff-Nielsen [Biometrika 70, 343–365 (1983; Zbl 0532.62006)], D. R. Cox and N. Reid [J. R. Stat. Soc., Ser. B 55, No. 2, 467–471 (1993; Zbl 0797.62015)], D. A. S. Fraser and N. Reid [Util. Math. 47, 33–53 (1995; Zbl 0829.62006); with J. Wu, Biometrika 86, No. 2, 249–264 (1999; Zbl 0932.62003)], and T. A. Severini [ibid. 86, No. 2, 235–247 (1999; Zbl 0943.62016)]. We consider inference on the generalized Pareto distribution shape parameter, the scale parameter being a nuisance parameter. Bootstrap-based testing inference is also considered. Monte Carlo simulation results on the finite sample performances of the usual profile maximum likelihood estimator and profile likelihood ratio test and also their modified versions is presented and discussed. The numerical evidence favors the modified profile maximum likelihood estimators and tests we propose. Finally, we consider two real datasets as illustrations. Cited in 1 Document MSC: 62E15 Exact distribution theory in statistics 62F10 Point estimation 62F03 Parametric hypothesis testing 60E05 Probability distributions: general theory 62P12 Applications of statistics to environmental and related topics Keywords:bootstrap; generalized Pareto distribution; likelihood ratio test; maximum likelihood estimation; profile likelihood Citations:Zbl 0532.62006; Zbl 0797.62015; Zbl 0829.62006; Zbl 0932.62003; Zbl 0943.62016 Software:ismev; Ox PDF BibTeX XML Cite \textit{J. F. Pires} et al., Braz. J. Probab. Stat. 32, No. 1, 69--85 (2018; Zbl 1404.62020) Full Text: DOI Euclid OpenURL References: [1] Barndorff-Nielsen, O. (1983). On a formula to the distribution of the maximum likelihood estimator. Biometrika70, 343–365. · Zbl 0532.62006 [2] Castillo, E. and Hadi, A. S. (1997). Fitting the generalized Pareto distribution to data. Journal of the American Statistical Association92, 1609–1620. · Zbl 0919.62014 [3] Castillo, E., Hadi, A. S., Balakrishnan, N. and Sarabia, J. M. (2005). Extreme Value and Related Models with Applications in Engineering and Science. Hoboken, NJ: Wiley. · Zbl 1072.62045 [4] Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. London: Springer. · Zbl 0980.62043 [5] Cox, D. and Hinkley, D. (1974). Theoretical Statistics. London: Chapman & Hall. · Zbl 0334.62003 [6] Cox, D. R. and Reid, N. (1987). Parameter orthogonality and approximate conditional inference. Journal of the Royal Statistical Society. Series B49, 1–39. · Zbl 0616.62006 [7] Cox, D. R. and Reid, N. (1993). A note on the calculation of adjusted profile likelihood. Journal of the Royal Statistical Society. Series B55, 467–471. · Zbl 0797.62015 [8] Cox, D. R. and Snell, E. J. (1968). A general definition of residuals. Journal of the Royal Statistical Society. Series B30, 248–275. · Zbl 0164.48903 [9] Davison, A. C. (2003). Statistical Models. Cambridge: Cambridge Univ. Press. · Zbl 1044.62001 [10] de Carvalho, M., Turkman, K. F. and Rua, A. (2013). Dynamic threshold modelling and the US business cycle. Journal of the Royal Statistical Society: Series C (Applied Statistics)62, 535–550. [11] Doornik, J. A. (2013). An Object-Oriented Matrix Language Ox 7. London: Timberlake Consultants. Available at http://www.doornik.com/. [12] Efron, B. (1979). Bootstrap methods: Another look at the jackknife. The Annals of Statistics7, 1–26. · Zbl 0406.62024 [13] Ferreira, A. and Haan, L. (2014). The generalized Pareto process; with a view towards application and simulation. Bernoulli20, 1717–1737. · Zbl 1312.60068 [14] Fraser, D. A. S. and Reid, N. (1995). Ancillaries and third-order significance. Utilitas Mathematica47, 33–53. · Zbl 0829.62006 [15] Fraser, D. A. S., Reid, N. and Wu, J. (1999). A simple general formula for tail probabilities for frequentist and Bayesian inference. Biometrika86, 249–264. · Zbl 0932.62003 [16] Hosking, J. R. M. and Wallis, J. R. (1987). Parameter and quantile estimation for the generalized Pareto distribution. Technometrics29, 339–349. · Zbl 0628.62019 [17] Nocedal, J. and Wright, S. J. (2006). Numerical Optimization. New York: Springer. · Zbl 1104.65059 [18] Pace, L. and Salvan, A. (1997). Principles of Statistical Inference from a Neo-Fisherian Perspective. Singapore: World Scientific. · Zbl 0911.62003 [19] Pickands, J. (1975). Statistical inference using extreme order statistics. The Annals of Statistics3, 119–131. · Zbl 0312.62038 [20] Severini, T. A. (1999). An empirical adjustment to the likelihood ratio statistic. Biometrika86, 235–247. · Zbl 0943.62016 [21] Severini, T. This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.