TL-moments and LQ-moments of the Exponentiated generalized extreme value distribution (EGEV) will be obtained and used to estimate the unknown parameters of the EGEV distribution. Many special cases may be obtained such as the L-moments, LH-moments and LL-moments. The estimation of the EGEV distribution parameters is studied in a numerical example where method of TL-moments compares to other estimation methods (L-moments estimators, LQ-moment estimators and the method of moment estimators). The true formulas for the rth classical moments and the probability weighted moments for the EGEV distribution will be obtained to correct the Adeyemi and Adebanji (2006) results
In this thesis, we have studied L-moments and trimmed L-moments (TL-moments) which are both linear f...
The method of LQ-moments (LQMOM) for estimating parameters and quantiles of the Generalized Logistic...
The vanilla method in univariate extreme-value theory consists of fitting the three-parameter Genera...
TL-moments and LQ-moments of the exponentiated generalized extreme value distribution (EGEV) will be...
AbstractTL-moments and LQ-moments of the exponentiated generalized extreme value distribution (EGEV)...
The LQ-moments are analogous to L-moments, found always exists, easier to compute and have the same ...
Statistical analysis of extremes is conducted for predicting large return periods events. LQ-moments...
International audienceFollowing the work of Azzalini ([2] and [3]) on the skew normal distribution, ...
Available from British Library Lending Division - LD:7520.345(89) / BLDSC - British Library Document...
Statistical analysis of extremes is conducted for predicting large return periods events. LQ-moments...
Copyright © 2013 Jong-WuuWu et al. This is an open access article distributed under the Creative Com...
Abstract. Following the work of Azzalini ([2] and [3]) on the skew normal distribution, we propose a...
To overcome drawbacks of central moments and comoment matrices usually used to characterize univaria...
This paper deals with properties of the exponentiated extreme value distribution. We derive the appr...
A parameter estimation method is proposed for fitting the generalized extreme value (GEV) distributi...
In this thesis, we have studied L-moments and trimmed L-moments (TL-moments) which are both linear f...
The method of LQ-moments (LQMOM) for estimating parameters and quantiles of the Generalized Logistic...
The vanilla method in univariate extreme-value theory consists of fitting the three-parameter Genera...
TL-moments and LQ-moments of the exponentiated generalized extreme value distribution (EGEV) will be...
AbstractTL-moments and LQ-moments of the exponentiated generalized extreme value distribution (EGEV)...
The LQ-moments are analogous to L-moments, found always exists, easier to compute and have the same ...
Statistical analysis of extremes is conducted for predicting large return periods events. LQ-moments...
International audienceFollowing the work of Azzalini ([2] and [3]) on the skew normal distribution, ...
Available from British Library Lending Division - LD:7520.345(89) / BLDSC - British Library Document...
Statistical analysis of extremes is conducted for predicting large return periods events. LQ-moments...
Copyright © 2013 Jong-WuuWu et al. This is an open access article distributed under the Creative Com...
Abstract. Following the work of Azzalini ([2] and [3]) on the skew normal distribution, we propose a...
To overcome drawbacks of central moments and comoment matrices usually used to characterize univaria...
This paper deals with properties of the exponentiated extreme value distribution. We derive the appr...
A parameter estimation method is proposed for fitting the generalized extreme value (GEV) distributi...
In this thesis, we have studied L-moments and trimmed L-moments (TL-moments) which are both linear f...
The method of LQ-moments (LQMOM) for estimating parameters and quantiles of the Generalized Logistic...
The vanilla method in univariate extreme-value theory consists of fitting the three-parameter Genera...