TY - JOUR

T1 - Maximum likelihood estimation of extreme value index for irregular cases

AU - Peng, Liang

AU - Qi, Yongcheng

PY - 2009/9/1

Y1 - 2009/9/1

N2 - A method in analyzing extremes is to fit a generalized Pareto distribution to the exceedances over a high threshold. By varying the threshold according to the sample size [Smith, R.L., 1987. Estimating tails of probability distributions. Ann. Statist. 15, 1174-1207] and [Drees, H., Ferreira, A., de Haan, L., 2004. On maximum likelihood estimation of the extreme value index. Ann. Appl. Probab. 14, 1179-1201] derived the asymptotic properties of the maximum likelihood estimates (MLE) when the extreme value index is larger than - frac(1, 2). Recently Zhou [2009. Existence and consistency of the maximum likelihood estimator for the extreme value index. J. Multivariate Anal. 100, 794-815] showed that the MLE is consistent when the extreme value index is larger than - 1. In this paper, we study the asymptotic distributions of MLE when the extreme value index is in between - 1 and - frac(1, 2) (including - frac(1, 2)). Particularly, we consider the MLE for the endpoint of the generalized Pareto distribution and the extreme value index and show that the asymptotic limit for the endpoint estimate is non-normal, which connects with the results in Woodroofe [1974. Maximum likelihood estimation of translation parameter of truncated distribution II. Ann. Statist. 2, 474-488]. Moreover, we show that same results hold for estimating the endpoint of the underlying distribution, which generalize the results in Hall [1982. On estimating the endpoint of a distribution. Ann. Statist. 10, 556-568] to irregular case, and results in Woodroofe [1974. Maximum likelihood estimation of translation parameter of truncated distribution II. Ann. Statist. 2, 474-488] to the case of unknown extreme value index.

AB - A method in analyzing extremes is to fit a generalized Pareto distribution to the exceedances over a high threshold. By varying the threshold according to the sample size [Smith, R.L., 1987. Estimating tails of probability distributions. Ann. Statist. 15, 1174-1207] and [Drees, H., Ferreira, A., de Haan, L., 2004. On maximum likelihood estimation of the extreme value index. Ann. Appl. Probab. 14, 1179-1201] derived the asymptotic properties of the maximum likelihood estimates (MLE) when the extreme value index is larger than - frac(1, 2). Recently Zhou [2009. Existence and consistency of the maximum likelihood estimator for the extreme value index. J. Multivariate Anal. 100, 794-815] showed that the MLE is consistent when the extreme value index is larger than - 1. In this paper, we study the asymptotic distributions of MLE when the extreme value index is in between - 1 and - frac(1, 2) (including - frac(1, 2)). Particularly, we consider the MLE for the endpoint of the generalized Pareto distribution and the extreme value index and show that the asymptotic limit for the endpoint estimate is non-normal, which connects with the results in Woodroofe [1974. Maximum likelihood estimation of translation parameter of truncated distribution II. Ann. Statist. 2, 474-488]. Moreover, we show that same results hold for estimating the endpoint of the underlying distribution, which generalize the results in Hall [1982. On estimating the endpoint of a distribution. Ann. Statist. 10, 556-568] to irregular case, and results in Woodroofe [1974. Maximum likelihood estimation of translation parameter of truncated distribution II. Ann. Statist. 2, 474-488] to the case of unknown extreme value index.

KW - Endpoint

KW - Extreme value index

KW - Generalized Pareto distribution

KW - Stable law

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U2 - 10.1016/j.jspi.2009.03.012

DO - 10.1016/j.jspi.2009.03.012

M3 - Article

AN - SCOPUS:67349089264

SN - 0378-3758

VL - 139

SP - 3361

EP - 3376

JO - Journal of Statistical Planning and Inference

JF - Journal of Statistical Planning and Inference

IS - 9

ER -