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 ...

In linear regression with functional predictors and scalar responses, it may be advantageous, particularly if the function is thought to contain features at many scales, to restrict the coefficient ...

The purpose of statistical model selection is to identify a parsimonious model, which is a model that is as simple as possible while maintaining good predictive ability over the outcome of interest.

• 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, ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's income based on their age, weight, current bank account ...

TUESDAY, May 27, 2025 (HealthDay News) -- The least absolute shrinkage and selection operator-logistic regression (Lasso-LR) model is optimal for predicting in-hospital mortality for adult patients ...

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, ...