Maximum Likelihood Estimation of Asymmetric Double Type II Pareto Distributions

Halvarsson, Daniel

doi:10.1007/s42519-019-0080-5

Cited by 3 publications

(1 citation statement)

References 26 publications

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“…Nadarajah et al. ( 2013 ) presented a double generalized Pareto distribution and Halvarsson ( 2020 ) studied double Pareto type II distribution. Armagan et al.…”

Section: Introductionmentioning

confidence: 99%

Double Inverse-Gaussian Distributions and Associated Inference

Almutairi

Ghitany

Alothman

et al. 2023

J Indian Soc Probab Stat

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In order to have more flexibility, several double distributions have been studied in the literature. In this paper, we propose a double inverse Gaussian distribution using random sign mixture transform and study its associated inferences. The maximum likelihood estimation is performed to estimate the parameters. Extensive simulation studies are carried out to examine the performance of the estimators and the corresponding confidence intervals of the parameters. A real data set example is presented to illustrate the procedure.

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“…Nadarajah et al. ( 2013 ) presented a double generalized Pareto distribution and Halvarsson ( 2020 ) studied double Pareto type II distribution. Armagan et al.…”

Section: Introductionmentioning

confidence: 99%

Double Inverse-Gaussian Distributions and Associated Inference

Almutairi

Ghitany

Alothman

et al. 2023

J Indian Soc Probab Stat

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A Maximum Entropy Method for the Prediction of Size Distributions

Metzig

Colijn

2020

Entropy

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We propose a method to derive the stationary size distributions of a system, and the degree distributions of networks, using maximisation of the Gibbs-Shannon entropy. We apply this to a preferential attachment-type algorithm for systems of constant size, which contains exit of balls and urns (or nodes and edges for the network case). Knowing mean size (degree) and turnover rate, the power law exponent and exponential cutoff can be derived. Our results are confirmed by simulations and by computation of exact probabilities. We also apply this entropy method to reproduce existing results like the Maxwell-Boltzmann distribution for the velocity of gas particles, the Barabasi-Albert model and multiplicative noise systems.

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A Bimodal Extension of the Log-Normal Distribution on the Real Line with an Application to DNA Microarray Data

Alfahad,

Ghitany,

Alothman

et al. 2023

Mathematics

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A bimodal double log-normal distribution on the real line is proposed using the random sign mixture transform. Its associated statistical inferences are derived. Its parameters are estimated by the maximum likelihood method. The performance of the estimators and the corresponding confidence intervals is checked by simulation studies. Application of the proposed distribution to a real data set from a DNA microarray is presented.

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Maximum Likelihood Estimation of Asymmetric Double Type II Pareto Distributions

Cited by 3 publications

References 26 publications

Double Inverse-Gaussian Distributions and Associated Inference

Double Inverse-Gaussian Distributions and Associated Inference

A Maximum Entropy Method for the Prediction of Size Distributions

A Bimodal Extension of the Log-Normal Distribution on the Real Line with an Application to DNA Microarray Data

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