Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

The least absolute shrinkage and selection operator ('lasso') has been widely used in regression shrinkage and selection. We extend its application to the regression model with autoregressive errors.

Estimating the conditional quantiles of outcome variables of interest is frequent in many research areas, and quantile regression is foremost among the utilized methods. The coefficients of a quantile ...

The goal of a machine learning regression problem is to predict a single numeric value. There are roughly a dozen different regression techniques such as basic linear regression, k-nearest neighbors ...