TY - JOUR
T1 - Iterative Estimation of the Extreme Value Index
AU - Mueller, S.
AU - Husler, J.
PY - 2005
Y1 - 2005
N2 - Let {X-n, n >= 1} be a sequence of independent random variables with common continuous distribution function F having finite and unknown upper endpoint. A new iterative estimation procedure for the extreme value index gamma is proposed and one implemented iterative estimator is investigated in detail, which is asymptotically as good as the uniform minimum varianced unbiased estimator in an ideal model. Moreover, the superiority of the iterative estimator over its non iterated counterpart in the non asymptotic case is shown in a simulation study.
AB - Let {X-n, n >= 1} be a sequence of independent random variables with common continuous distribution function F having finite and unknown upper endpoint. A new iterative estimation procedure for the extreme value index gamma is proposed and one implemented iterative estimator is investigated in detail, which is asymptotically as good as the uniform minimum varianced unbiased estimator in an ideal model. Moreover, the superiority of the iterative estimator over its non iterated counterpart in the non asymptotic case is shown in a simulation study.
U2 - 10.1007/s11009-005-1487-x
DO - 10.1007/s11009-005-1487-x
M3 - Article
SN - 1387-5841
VL - 7
SP - 139
EP - 148
JO - Methodology and Computing in Applied Probability
JF - Methodology and Computing in Applied Probability
ER -