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 [PDF]
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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Power Prior Elicitation in Bayesian Quantile Regression [PDF]
Journal of Probability and Statistics, 2011 We address a quantile dependent prior for Bayesian quantile regression. We extend the idea of the power prior distribution in Bayesian quantile regression by employing the likelihood function that is based on a location-scale mixture representation of ...
Rahim Alhamzawi, Keming Yu
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Simulation Study The Using of Bayesian Quantile Regression in Nonnormal Error [PDF]
Cauchy: Jurnal Matematika Murni dan Aplikasi, 2018 The purposes of this paper is to introduce the ability of the Bayesian quantile regression method in overcoming the problem of the nonnormal errors using asymmetric laplace distribution on simulation study.
Catrin Muharisa +2 more
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Comparison of Bayesian and frequentist quantile regressions in studying the trend of discharge changes in several hydrometric stations of the Gorganroud basin in Iran [PDF]
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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Investigation into Interactions between Accident Consequences and Traffic Signs: A Bayesian Bivariate Tobit Quantile Regression Approach [PDF]
Journal of Advanced Transportation, 2018 This study intended to investigate the interactions between accident severity levels and traffic signs in state roads located in Croatia and explore the correlation between accident severity levels and heterogeneity attributed to unobserved factors.
Xuecai Xu, Željko Šarić
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A Bayesian hurdle quantile regression model for citation analysis with mass points at lower values
Quantitative Science Studies, 2021 Quantile regression presents a complete picture of the effects on the location, scale, and shape of the dependent variable at all points, not just the mean.
Marzieh Shahmandi +2 more
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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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Variational Bayesian Inference for Quantile Regression Models with Nonignorable Missing Data [PDF]
Mathematics, 2023 Quantile regression models are remarkable structures for conducting regression analyses when the data are subject to missingness. Missing values occur because of various factors like missing completely at random, missing at random, or missing not at ...
Xiaoning Li, Mulati Tuerde, Xijian Hu
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BarekengThe poverty line is the threshold income level below which a person or household is considered to be living in poverty. The poverty line is a representation of the minimum rupiah amount needed to meet the minimum basic food needs equivalent to 2100 ...
Lilis Harianti Hasibuan +4 more
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