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Bayesian nonparametric quantile mixed-effects models via regularization using Gaussian process priors
In this study, we proposed using Bayesian nonparametric quantile mixed-effects models (BNQMs) to estimate the nonlinear structure of quantiles in...
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Quantile Estimation in a Generalized Asymmetric Distributional Setting
Allowing for symmetry in distributionsGijbels, Irène is often a necessity inKarim, Rezaul statistical modelling. This paper studies a broad...
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Distributional Regression Models
Essentially, all regression models that we have dealt with thus far have been mean regression models since they relate the predictor...
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Logistic Quantile Regression for Bounded Outcomes Using a Family of Heavy-Tailed Distributions
Mean regression model could be inadequate if the probability distribution of the observed responses is not symmetric. Under such situation, the...
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A Comparison of Estimation Methods for Shared Gamma Frailty Models
This paper compares six different estimation methods for shared frailty models via a series of simulation studies. A shared frailty model is a...
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Computing Finite Mixture Estimators in the Tails
The finite mixtures approach identifies homogeneous groups within the sample. The data are aggregated into classes sharing similar patterns without...
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Estimation of Bergsma’s covariance
Bergsma (A new correlation coefficient, its orthogonal decomposition and associated tests of independence, ar**v preprint
ar**v:math/0604627 ...
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A modeler’s guide to extreme value software
This review paper surveys recent development in software implementations for extreme value analyses since the publication of Stephenson and Gilleland...
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Robust mixture regression modeling based on two-piece scale mixtures of normal distributions
The inference of mixture regression models (MRM) is traditionally based on the normal (symmetry) assumption of component errors and thus is sensitive...
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Exclusive Topic Model
Digital documents are generated, disseminated, and disclosed in books, research papers, newspapers, online feedback, and other content containing...
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Nonparametric tests for combined location-scale and Lehmann alternatives using adaptive approach and max-type metric
The paper deals with the classical two-sample problem for the combined location-scale and Lehmann alternatives, known as the versatile alternative....
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A new quantile regression model with application to human development index
A new odd log-logistic unit omega distribution is defined and studied, and some of its structural properties are obtained. A quantile regression...
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Approximate Inferences for Nonlinear Mixed Effects Models with Scale Mixtures of Skew-Normal Distributions
Nonlinear mixed effects models have received a great deal of attention in the statistical literature in recent years because of their flexibility in...
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Functional Linear Partial Quantile Regression with Guaranteed Convergence for Neuroimaging Data Analysis
Functional data such as curves and surfaces have become more and more common with modern technological advancements. The use of functional predictors...
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Multivariate Skewness and Kurtosis
A unified treatment of all currently available cumulant-based indices of multivariate skewness and kurtosis is provided in this chapter. They are...
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LRD spectral analysis of multifractional functional time series on manifolds
This paper addresses the estimation of the second-order structure of a manifold cross-time random field (RF) displaying spatially varying Long Range...
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Multivariate Skew Distributions
In this chapter we provide a systematic treatment of several multivariate skew distributions. General formulae for cumulant vectors at least up to...
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Some Bivariate and Multivariate Models Involving Independent Gamma Distributed Components
Several multivariate models involving independent gamma distributed components (three of which are new) are described. The flexible bivariate beta(2)...
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Bayesian joint inference for multivariate quantile regression model with L\(_{1/2}\) penalty
This paper considers a Bayesian approach for joint estimation of the marginal conditional quantiles from several dependent variables under a linear...
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On Mean And/or Variance Mixtures of Normal Distributions
Parametric distributions are an important part of statistics. There is now a voluminous literature on different fascinating formulations of flexible...