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The exponentiated generalized inverse Gaussian distribution
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Artur Lemonte, Gauss Cordeiro
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A new generalized inverse Gaussian distribution with Bayesian estimators
A new family of distributions, called the transformed inverse Gaussian (TIG) distribution with four parameters, is introduced. Within this family, a specific distribution called the new generalized inverse Gaussian (NGIG) distribution, with three ...
Kenneth Goward +3 more
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Konzou, Essomanda +2 more
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Promotion time cure model with generalized Poisson-Inverse Gaussian Distribution
Background & Aim: In the survival data with Long-term survivors the event has not occurred for all the patients despite long-term follow-up, so the survival time for a certain percent is censored at the end of the study.
Mitra Rahimzadeh, Behrooz Kavehie
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Generalized Sichel Distribution and Associated Inference [PDF]
In this paper, we propose a generalized form of Sichel distribution which is obtained by mixing the Poisson distribution with the extended generalized inverse Gaussian distribution.
Yeh Ching Low +2 more
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On Free Generalized Inverse Gaussian Distributions [PDF]
We study here properties of free Generalized Inverse Gaussian distributions (fGIG) in free probability. We show that in many cases the fGIG shares similar properties with the classical GIG distribution. In particular we prove that fGIG is freely infinitely divisible, free regular and unimodal, and moreover we determine which distributions in this class
Hasebe, Takahiro, Szpojankowski, Kamil
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Discrimination between Some Over Dispersed Count Distributions
The Poisson inverse Gaussian and generalized Poisson distributions are widely used in modelling overdispersed count data which are commonly found in healthcare, insurance, engineering, econometric and ecology.
Yook-Ngor Phang +2 more
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Improved Particle Filter for Non-Gaussian Forecasting-aided State Estimation
Gaussian assumptions of non-Gaussian noises hinder the improvement of state estimation accuracy. In this paper, an asymmetric generalized Gaussian distribution (AGGD), as a unified representation of various unimodal distributions, is applied to formulate
Lyuzerui Yuan +3 more
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Gibbs Sampler for Matrix Generalized Inverse Gaussian Distributions
Sampling from matrix generalized inverse Gaussian (MGIG) distributions is required in Markov Chain Monte Carlo (MCMC) algorithms for a variety of statistical models. However, an efficient sampling scheme for the MGIG distributions has not been fully developed.
Yasuyuki Hamura +2 more
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The Prediction of the Maternal and Fetal Blood Lead Level via Generalized Linear Model [PDF]
Generalized linear models (GLMs) are generalization of the linear regression models, which allow fitting regression models to response variable that is non normal and follows a general exponential family.
Zakaria Y. AL-Jammal
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