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Crisci, C., Perera, G. and Sampognaro, L. (2023) Goodness-of-Fit Test for Non-Stationary and Strongly Dependent Samples. Advances in Pure Mathematics, 13, 226-236.
https://doi.org/10.4236/apm.2023.135016

has been cited by the following article:

• TITLE: Estimating the Components of a Mixture of Extremal Distributions under Strong Dependence

  AUTHORS: Carolina Crisci, Gonzalo Perera, Lia Sampognaro

  KEYWORDS: Mixture of Extremal Distributions, Strongly Dependent Data

  JOURNAL NAME: Advances in Pure Mathematics, Vol.13 No.7, July 12, 2023

  ABSTRACT: In this paper, we provide a method based on quantiles to estimate the parameters of a finite mixture of Fréchet distributions, for a large sample of strongly dependent data. This is a situation that appears when dealing with environmental data and there was a real need of such method. We validate our approach by means of estimation and goodness-of-fit testing over simulated data, showing an accurate performance.