Modelling of South African Hypertension: Comparative Analysis of the Classical and Bayesian Quantile Regression Approaches [PDF]
Inquiry: The Journal of Health Care Organization, Provision, and Financing, 2022 Hypertension has become a major public health challenge and a crucial area of research due to its high prevalence across the world including the sub-Saharan Africa.
Anesu Gelfand Kuhudzai PhD candidate +3 more
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High-Dimensional Variable Selection for Quantile Regression Based on Variational Bayesian Method
Mathematics, 2023 The quantile regression model is widely used in variable relationship research of moderate sized data, due to its strong robustness and more comprehensive description of response variable characteristics.
Dengluan Dai, Anmin Tang, Jinli Ye
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Modeling Spatial Data with Heteroscedasticity Using PLVCSAR Model: A Bayesian Quantile Regression Approach [PDF]
EntropySpatial data not only enables smart cities to visualize, analyze, and interpret data related to location and space, but also helps departments make more informed decisions.
Rongshang Chen, Zhiyong Chen
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U-shaped association between dietary flavonoid and gallstone prevalence with sex-specific effects: Insights from a cross-sectional study [PDF]
Journal of International Medical ResearchObjective To examine the association between dietary flavonoid intake and gallstone prevalence in a representative United States sample using National Health and Nutrition Examination Survey 2017–2018 data.
Jiaying Lin +4 more
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Modified Quantile Regression for Modeling the Low Birth Weight
Frontiers in Applied Mathematics and Statistics, 2022 This study aims to identify the best model of low birth weight by applying and comparing several methods based on the quantile regression method's modification.
Ferra Yanuar +2 more
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Cauchy: Jurnal Matematika Murni dan Aplikasi, 2021 This study aims to construct the model for the length of hospital stay for patients with COVID-19 using quantile regression and Bayesian quantile approaches.
Ferra Yanuar +4 more
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Journal of Water and Climate Change, 2023 This research utilized Bayesian and quantile regression techniques to analyze trends in discharge levels across various seasons for three stations in the Gorganroud basin of northern Iran. The study spanned a period of 50 years (1966–2016).
Khalil Ghorbani +3 more
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Simulation Study of Autocorrelated Error Using Bayesian Quantile Regression
Science and Technology Indonesia, 2020 The purpose of this study is to compare the ability of the Classical Quantile Regression method and the Bayesian Quantile Regression method in estimating models that contain autocorrelated error problems using simulation studies.
Nayla Desviona, Ferra Yanuar
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qgam: Bayesian Nonparametric Quantile Regression Modeling in R
Journal of Statistical Software, 2021 Generalized additive models (GAMs) are flexible non-linear regression models, which can be fitted efficiently using the approximate Bayesian methods provided by the mgcv R package.
Matteo Fasiolo +4 more
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Bayesian quantile semiparametric mixed-effects double regression models
Statistical Theory and Related Fields, 2021 Semiparametric mixed-effects double regression models have been used for analysis of longitudinal data in a variety of applications, as they allow researchers to jointly model the mean and variance of the mixed-effects as a function of predictors ...
Duo Zhang +3 more
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