Estimation of second order parameters using probability weighted moments
ESAIM: Probability and Statistics, Tome 16 (2012), pp. 97-113.

Voir la notice de l'article provenant de la source Numdam

The P.O.T. method (Peaks Over Threshold) consists in using the generalized Pareto distribution (GPD) as an approximation for the distribution of excesses over a high threshold. In this work, we use a refinement of this approximation in order to estimate second order parameters of the model using the method of probability-weighted moments (PWM): in particular, this leads to the introduction of a new estimator for the second order parameter ρ, which will be compared to other recent estimators through some simulations. Asymptotic normality results are also proved. Our new estimator of ρ looks especially competitive when  |ρ|  is small.

DOI : 10.1051/ps/2010017
Classification : 62G32, 60G70
Keywords: extreme values, domain of attraction, excesses, generalized Pareto distribution, probability-weighted moments, second order parameter, third order condition
@article{PS_2012__16__97_0,
     author = {Worms, Julien and Worms, Rym},
     title = {Estimation of second order parameters using probability weighted moments},
     journal = {ESAIM: Probability and Statistics},
     pages = {97--113},
     publisher = {EDP-Sciences},
     volume = {16},
     year = {2012},
     doi = {10.1051/ps/2010017},
     mrnumber = {2946122},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.1051/ps/2010017/}
}
TY  - JOUR
AU  - Worms, Julien
AU  - Worms, Rym
TI  - Estimation of second order parameters using probability weighted moments
JO  - ESAIM: Probability and Statistics
PY  - 2012
SP  - 97
EP  - 113
VL  - 16
PB  - EDP-Sciences
UR  - http://geodesic.mathdoc.fr/articles/10.1051/ps/2010017/
DO  - 10.1051/ps/2010017
LA  - en
ID  - PS_2012__16__97_0
ER  - 
%0 Journal Article
%A Worms, Julien
%A Worms, Rym
%T Estimation of second order parameters using probability weighted moments
%J ESAIM: Probability and Statistics
%D 2012
%P 97-113
%V 16
%I EDP-Sciences
%U http://geodesic.mathdoc.fr/articles/10.1051/ps/2010017/
%R 10.1051/ps/2010017
%G en
%F PS_2012__16__97_0
Worms, Julien; Worms, Rym. Estimation of second order parameters using probability weighted moments. ESAIM: Probability and Statistics, Tome 16 (2012), pp. 97-113. doi : 10.1051/ps/2010017. http://geodesic.mathdoc.fr/articles/10.1051/ps/2010017/

[1] A. Balkema and L. De Haan, Residual life time at a great age. Ann. Probab. 2 (1974) 792-801. | Zbl

[2] F. Caeiro, M.I. Gomes and D. Pestana, A note on the asymptotic variance at optimal levels of a bias-corrected Hill estimator. Stat. Probab. Lett. 79 (2009) 295-303. | Zbl | MR

[3] G. Ciuperca and C. Mercadier, Semi-parametric estimation for heavy tailed distributions. Extremes 13 (2010) 55-87. | Zbl | MR

[4] J. Diebolt, A. Guillou and R. Worms, Asymptotic behaviour of the probability-weighted moments and penultimate approximation. ESAIM : PS 7 (2003) 217-236. | Zbl | MR | mathdoc-id

[5] J. Diebolt, A. Guillou and I. Rached, Approximation of the distribution of excesses through a generalized probability-weighted moments method. J. Statist. Plann. Inference 137 (2007) 841-857. | Zbl | MR

[6] J. Diebolt, A. Guillou and I. Rached, Approximation of the distribution of excesses through a generalized probability-weighted moments method. J. Statist. Plann. Inference 137 (2007) 841-857. | Zbl | MR

[7] H. Drees and E. Kaufmann, Selecting the optimal sample fraction in univariate extreme value estimation. Stoc. Proc. Appl. 75 (1998) 149-172. | Zbl | MR

[8] M.I. Fraga Alves, L. De Haan and T. Lin, Estimation of the parameter controlling the speed of convergence in extreme value theory. Math. Methods Stat. 12 (2003) 155-176. | MR

[9] M.I. Fraga Alves, M.I. Gomes and L. De Haan, A new class of semi-parametric estimators of the second order parameter. Portugaliae Mathematica 60 (2003) 193-213. | Zbl | MR

[10] M.I. Fraga Alves, L. De Haan and T. Lin, Third order extended regular variation. Publ. Inst. Math. 80 (2006) 109-120. | Zbl | MR

[11] M.I. Fraga Alves, M.I. Gomes, L. De Haan and C. Neves, A note on second order conditions in extreme value theory : linking general and heavy tail conditions. REVSTAT Stat. J. 5 (2007) 285-304. | Zbl | MR

[12] M.I. Gomes and J. Martins, “Asymptotically unbiased” estimators of the tail index based on external estimation of the second order parameter. Extremes 5 (2002) 5-31. | Zbl | MR

[13] M.I. Gomes, L. De Haan and L. Peng, Semi-parametric estimation of the second order parameter in statistics of extremes. Extremes 5 (2002) 387-414. | Zbl | MR

[14] P. Hall and A.H. Welsh, Adaptive estimates of parameters of regular variation. Ann. Stat. 13 (1985) 331-341. | Zbl | MR

[15] J. Hosking and J. Wallis, Parameter and quantile estimation for the generalized Pareto distribution. Technometrics 29 (1987) 339-349. | Zbl | MR

[16] L. Peng, Asymptotically unbiased estimator for the extreme value index. Statist. Prob. Lett. 38 (1998) 107-115. | Zbl | MR

[17] J. Pickands Iii, Statistical inference using extreme order statistics. Ann. Statist. 3 (1975) 119-131. | Zbl | MR

[18] J.P. Raoult and R. Worms, Rate of convergence for the generalized Pareto approximation of the excesses. Adv. Applied Prob. 35 (2003) 1007-1027. | Zbl | MR

[19] R.J. Serfling, Approximation Theorems of Mathematical Statistics. Wiley & Son (1980). | Zbl | MR

[20] A.W. Van Der Vaart, Asymptotic Statistics. Cambridge Series in Statistical and Probabilistic Mathematics (2000). | Zbl

[21] R. Worms, Penultimate approximation for the distribution of the excesses. ESAIM : PS 6 (2002) 21-31. | Zbl | MR | mathdoc-id

Cité par Sources :