Results 171 to 180 of about 44,356 (305)
A Bayesian Quantile Regression Analysis of Potential Risk Factors for Violent Crimes in USA
, 2012 Ming Wang, Lijun Zhang
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Bayesian Inference for Spatially‐Temporally Misaligned Data Using Predictive Stacking
Environmetrics, Volume 37, Issue 2, March 2026.ABSTRACT Air pollution remains a major environmental risk factor that is often associated with adverse health outcomes. However, quantifying and evaluating its effects on human health is challenging due to the complex nature of exposure data. Recent technological advances have led to the collection of various indicators of air pollution at increasingly
Soumyakanti Pan, Sudipto Banerjee
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Accounting for Missing Data When Modelling Block Maxima
Environmetrics, Volume 37, Issue 2, March 2026.ABSTRACT Modeling block maxima using the generalized extreme value (GEV) distribution is a classical and widely used method for studying univariate extremes. It allows for theoretically motivated estimation of return levels, including extrapolation beyond the range of observed data.
Emma S. Simpson, Paul J. Northrop
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Risk Margin Quantile Function via Parametric and Non-Parametric Bayesian Quantile Regression
, 2014 Alice X. D. Dong +2 more
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Spatial Distribution of Various forms of Malnutrition Among Reproductive Age Women in Nepal: A Bayesian Geoadditive Quantile Regression Approach [PDF]
, 2020 Richa Vatsa, Umesh Ghimire
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Bayesian inference for Lp–quantile regression models
, 2016 Lp–quantiles generalise quantiles and expectiles to account for the whole distribution of the random variable of interest. In this paper, we introduce the Lp– quantile regression model, we propose a collapsed Gibbs–sampler algorithm to make Bayesian inference on the regression parameters.
Bernardi, M. +2 more
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A New Unit‐Lindley Mixed‐Effects Model With an Application to Electricity Access Data
Environmetrics, Volume 37, Issue 2, March 2026.ABSTRACT This paper introduces a novel unit‐Lindley mixed‐effects model (NULMM) within the generalized linear mixed model (GLMM) framework, designed for analyzing correlated response variables bounded within the unit interval. Parameter estimation was conducted via maximum likelihood, using Laplace approximation and adaptive Gaussian‐ Hermite ...
Nirajan Bam +2 more
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Forecasting Carbon Prices: A Literature Review
Journal of Forecasting, Volume 45, Issue 2, Page 496-529, March 2026.ABSTRACT Carbon emissions trading is utilized by a growing number of states as a significant tool for addressing greenhouse gas emissions (GHG), global warming problem and the climate crisis. Accurate forecasting of carbon prices is essential for effective policy design and investment strategies in climate change mitigation.
Konstantinos Bisiotis +2 more
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