Displaying similar documents to “Asymptotic behaviour of the probability-weighted moments and penultimate approximation”

Improved inference for the generalized Pareto distribution under linear, power and exponential normalization

Osama Mohareb Khaled, Haroon Mohamed Barakat, Nourhan Khalil Rakha (2022)

Kybernetika

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We discuss three estimation methods: the method of moments, probability weighted moments, and L-moments for the scale parameter and the extreme value index in the generalized Pareto distribution under linear normalization. Moreover, we adapt these methods to use for the generalized Pareto distribution under power and exponential normalizations. A simulation study is conducted to compare the three methods on the three models and determine which is the best, which turned out to be the...

Asymptotic behaviour of the probability-weighted moments and penultimate approximation

Jean Diebolt, Armelle Guillou, Rym Worms (2003)

ESAIM: Probability and Statistics

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The P.O.T. (Peaks-Over-Threshold) approach consists of using the Generalized Pareto Distribution (GPD) to approximate the distribution of excesses over a threshold. We use the probability-weighted moments to estimate the parameters of the approximating distribution. We study the asymptotic behaviour of these estimators (in particular their asymptotic bias) and also the functional bias of the GPD as an estimate of the distribution function of the excesses. We adapt penultimate approximation...

What is the best approximation of ruin probability in infinite time?

Krzysztof Burnecki, Paweł Miśta, Aleksander Weron (2005)

Applicationes Mathematicae

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We compare 12 different approximations of ruin probability in infinite time studying typical light- and heavy-tailed claim size distributions, namely exponential, mixture of exponentials, gamma, lognormal, Weibull, loggamma, Pareto and Burr. We show that approximation based on the Pollaczek-Khinchin formula gives most accurate results, in fact it can be chosen as a reference method. We also introduce a promising modification to the De Vylder approximation.

A weighted version of Gamma distribution

Kanchan Jain, Neetu Singla, Rameshwar D. Gupta (2014)

Discussiones Mathematicae Probability and Statistics

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Weighted Gamma (WG), a weighted version of Gamma distribution, is introduced. The hazard function is increasing or upside-down bathtub depending upon the values of the parameters. This distribution can be obtained as a hidden upper truncation model. The expressions for the moment generating function and the moments are given. The non-linear equations for finding maximum likelihood estimators (MLEs) of parameters are provided and MLEs have been computed through simulations and also for...