Beside the model, the other input into a regression analysis is some relevant sample data, consisting of the observed values of the dependent and explanatory variables for a sample of members of the ...

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 first step in conducting a regression-based study is to specify a model. In real applications, this is usually the most challenging step - deciding which variables “belong” in the model and which ...

Linear models with linear equality constraints on the coefficients are translated into models with a singular design matrix and a nonsingular disturbances covariance matrix in order to deduce general ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 27, No. 1 (Mar., 1999), pp. 63-79 (17 pages) In some physical systems, where the goal is to describe behaviour over an ...

The application of Cox proportional hazards (CoxPH) models to survival data and the derivation of hazard ratio (HR) are well established. Although nonlinear, tree-based machine learning (ML) models ...