Journal of Hydrometeorology, Vol. 17, No. 6 (June 2016), pp. 1869-1883 (15 pages) ABSTRACT Classical regression models are widely used in hydrological regional frequency analysis (RFA) in order to ...
Bayesian quantile regression and statistical modelling represent a growing paradigm in contemporary data analysis, extending conventional regression by estimating various conditional quantiles rather ...
The goal of a machine learning regression problem is to predict a single numeric value. Quantile regression is a variation where you are concerned with under-prediction or over-prediction. I'll phrase ...
We study censored quantile regression with covariates measured with errors. We propose a composite quantile objective function based on inverse censoring-probability weighting, and an averaging ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback