Results 31 to 40 of about 44,356 (305)
Regularized Bayesian quantile regression [PDF]
Communications in Statistics - Simulation and Computation, 2017 A number of nonstationary models have been developed to estimate extreme events as function of covariates. A quantile regression (QR) model is a statistical approach intended to estimate and conduct inference about the conditional quantile functions.
Adlouni, Salaheddine El +2 more
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Bayesian Estimation of Partial Functional Tobit Censored Quantile Regression Model. [PDF]
Stat MedWang C, Lu Z, Wang C, Song X.
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Bayesian Endogenous Tobit Quantile Regression
Bayesian Analysis, 2016 This study proposes $p$-th Tobit quantile regression models with endogenous variables. In the first stage regression of the endogenous variable on the exogenous variables, the assumption that the $ $-th quantile of the error term is zero is introduced.
Genya Kobayashi
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A Bayesian Binary reciprocal LASSO quantile regression (with practical application)
Journal of Kufa for Mathematics and Computer, 2023 Quantile regression is one of the methods that has taken a wide space in application in the previous two decades because of the attractive features of these methods to researchers, as it is not affected by outliers values, meaning that it is considered ...
Mohammed Kahnger, Ahmad Naeem Flaih
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Posterior moments and quantiles for the normal location model with Laplace prior [PDF]
, 2020 We derive explicit expressions for arbitrary moments and quantiles of the posterior distribution of the location parameter eta in the normal location model with Laplace prior, and use the results to approximate the posterior distribution of sums of ...
Franco Peracchi +2 more
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Bayesian lasso binary quantile regression
Computational Statistics, 2013 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Benoit, Dries +2 more
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PLoS ONE, 2020 This paper presents a Bayesian analysis of linear mixed models for quantile regression based on a Cholesky decomposition for the covariance matrix of random effects.
Yonggang Ji, Haifang Shi
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Bayesian analysis of a Tobit quantile regression model [PDF]
, 2007 This paper develops a Bayesian framework for Tobit quantile regression. Our approach is organized around a likelihood function that is based on the asymmetric Laplace dis- tribution, a choice that turns out to be natural in this context.
Stander, J, Yu, K
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Anomaly Detection in Health Insurance Claims Using Bayesian Quantile Regression
International Journal of Mathematics and Mathematical Sciences, 2021 Research has shown that current health expenditure in most countries, especially in sub-Saharan Africa, is inadequate and unsustainable. Yet, fraud, abuse, and waste in health insurance claims by service providers and subscribers threaten the delivery of
Ezekiel N. N. Nortey +4 more
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Quantile Regression Neural Networks: A Bayesian Approach [PDF]
Journal of Statistical Theory and Practice, 2021 This article introduces a Bayesian neural network estimation method for quantile regression assuming an asymmetric Laplace distribution (ALD) for the response variable. It is shown that the posterior distribution for feedforward neural network quantile regression is asymptotically consistent under a misspecified ALD model. This consistency proof embeds
S. R. Jantre, S. Bhattacharya, T. Maiti
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