This paper proposes a regularized regression procedure for finding a predictive relation between one variable and a field of other variables. The procedure estimates a linear prediction model under ...

A research team shows that phenomic prediction, which integrates full multispectral and thermal information rather than ...

Many regression analyses involve explanatory variables that are measured with error, and failing to account for this error is well known to lead to biased point and ...

When you’re building a machine learning model you’re faced with the bias-variance tradeoff, where you have to find the balance between having a model that: Is very expressive and captures the real ...

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 ...