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 ...

That estimator extends to random fields with unspecified and possibly highly complex spatial dependence structure, the quantile regression methods considered in the context of independent samples or ...

Susanne M. Schénnach, Quantile Regression with Mismeasured Covariates, Econometric Theory, Vol. 24, No. 4 (Aug., 2008), pp. 1010-1043 ...

Scikit-learn, the popular Python-based machine learning (ML) library, has released version 1.0. Although the library has been stable for some time, and the release contains no breaking changes ...

Beta regression offers a robust framework for analysing data that are confined to the unit interval, enabling researchers to model proportions, probabilities, and other fractional outcomes with ...

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 ...