We consider the estimation of regression models on strata defined using a categorical covariate, in order to identify interactions between this categorical covariate and the other predictors. A basic ...

Imposition of a lasso penalty shrinks parameter estimates toward zero and performs continuous model selection. Lasso penalized regression is capable of handling linear regression problems where the ...

Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation Model selection and forecasting in stress tests can be facilitated using machine learning techniques. These techniques have ...

• A prediction model for assessing the risk of coagulation disorders after coronary artery bypass grafting (CABG) was developed and demonstrated good prediction performance in elderly individuals, ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...