This article suggests very simple three-step estimators for censored quantile regression models with a separation restriction on the censoring probability. The estimators are theoretically attractive ...

The objective function employed in the estimation can also be used to check inadequacy of a power-transformed linear quantile regression model and to obtain inference on the transformation parameter.

They are variations of linear regression (and therefore not very powerful) and are extremely difficult to train because they require linear programming (and therefore very complex). However, a ...

For example, adaptations of the unit Burr-XII distribution for quantile regression modelling have demonstrated enhanced flexibility in accommodating varying data dispersions and asymmetric shapes [2].

In this paper, we suggest to use quantile regression for survival data to quantify the long-term benefit of immunotherapy. Our motivation is that this approach is not trial-specific and provides ...

Bayesian Quantile Regression and Statistical Modelling Publication Trend The graph below shows the total number of publications each year in Bayesian Quantile Regression and Statistical Modelling.

According to a Bitcoin researcher, a quantile regression model indicates that there is a 99% percentile target for BTC at $275,000 by the end of November 2025.