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Double Inverse-Gaussian Distributions and Associated Inference
In order to have more flexibility, several double distributions have been studied in the literature. In this paper, we propose a double inverse...
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Multivariate mixed Poisson Generalized Inverse Gaussian INAR(1) regression
In this paper, we present a novel family of multivariate mixed Poisson-Generalized Inverse Gaussian INAR(1), MMPGIG-INAR(1), regression models for...
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Solving linear Bayesian inverse problems using a fractional total variation-Gaussian (FTG) prior and transport map
The Bayesian inference is widely used in many scientific and engineering problems, especially in the linear inverse problems in infinite-dimensional...
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Optimum test planning for heterogeneous inverse Gaussian processes
The heterogeneous inverse Gaussian (IG) process is one of the most popular and most considered degradation models for highly reliable products. One...
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Infinite Mixtures of Multivariate Normal-Inverse Gaussian Distributions for Clustering of Skewed Data
Mixtures of multivariate normal inverse Gaussian (MNIG) distributions can be used to cluster data that exhibit features such as skewness and heavy...
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Bayesian Linear Inverse Problems in Regularity Scales with Discrete Observations
We obtain rates of contraction of posterior distributions in inverse problems with discrete observations. In a general setting of smoothness scales...
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Sequential Estimation of an Inverse Gaussian Mean with Known Coefficient of Variation
This paper deals with develo** sequential procedures for estimating the mean of an inverse Gaussian (IG) distribution when the population...
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On estimating common mean of several inverse Gaussian distributions
Estimation of the common mean of inverse Gaussian distributions with different scale-like parameters is considered. We study finite sample...
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Bayesian Latent Gaussian Models
Bayesian latent Gaussian models are Bayesian hierarchical models that assign Gaussian prior densities to the latent parameters. In this chapter, we...
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Survival Analysis for the Inverse Gaussian Distribution: Natural Conjugate and Jeffrey’s Priors
This study focuses on the use of a Bayesian method to analyze survival data that follow an inverse Gaussian (IG) distribution. Both IG parameters are...
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An extended Langevinized ensemble Kalman filter for non-Gaussian dynamic systems
State estimation for large-scale non-Gaussian dynamic systems remains an unresolved issue, given nonscalability of the existing particle filter...
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Functional linear non-Gaussian acyclic model for causal discovery
In causal discovery, non-Gaussianity has been used to characterize the complete configuration of a linear non-Gaussian acyclic model (LiNGAM),...
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Optimal dichotomization of bimodal Gaussian mixtures
Despite criticism for loss of information and power, dichotomization of variables is still frequently used in social, behavioral, and medical...
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Spatial extremes and stochastic geometry for Gaussian-based peaks-over-threshold processes
Geometric properties of exceedance regions above a given quantile level provide meaningful theoretical and statistical characterizations for...
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Gaussian Distributions
This chapter is concerned with Gaussian distributions, either real Gaussian on...
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Bayesian Nonparametric Generative Modeling of Large Multivariate Non-Gaussian Spatial Fields
Multivariate spatial fields are of interest in many applications, including climate model emulation. Not only can the marginal spatial fields be...
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On the Gaussian representation of the Riesz probability distribution on symmetric matrices
The Riesz probability distribution on symmetric matrices represents an important extension of the Wishart distribution. It is defined by its Laplace...
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On Properties and Applications of Gaussian Subordinated Lévy Fields
We consider Gaussian subordinated Lévy fields (GSLFs) that arise by subordinating Lévy processes with positive transformations of Gaussian random...
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Gaussian quasi-information criteria for ergodic Lévy driven SDE
We consider relative model comparison for the parametric coefficients of an ergodic Lévy driven model observed at high-frequency. Our asymptotics is...
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A New Construction of Covariance Functions for Gaussian Random Fields
We develop a new approach to creating covariance functions for Gaussian random fields via point processes on the complex plane. We present two...
