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. The birth weight data is violated with ...

As one of the important statistical methods, quantile regression (QR) extends traditional regression analysis. In QR, various quantiles of the response variable are modeled as linear functions of the ...

Quantile regression offers a versatile framework for characterising the full conditional distribution of a response variable by modelling specified quantiles rather than the mean alone. This approach ...

Quantile regression models the relationship between a specified conditional quantile (or percentile) of a dependent (response) variable and one or more independent (explanatory) variables (Cade and ...

Abstract: In quantile regression models, numerous penalization methods have been developed to deal with ordinary least-squares method problems. Such methods are ridge penalized quantile regression, ...

When generating predictions about an output, it is sometimes useful to get a confidence score or, similarly, a range of values around this expected value in which the actual value might be found.