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 ...

Median regression models become an attractive alternative to mean regression models when employing flexible families of distributions for the errors. Classical ...

We present self-modeling regression models for flexible nonparametric modeling of multiple outcomes measured longitudinally. Based on penalized regression splines, the models borrow strength across ...

Dr. James McCaffrey of Microsoft Research explains how to evaluate, save and use a trained regression model, used to predict a single numeric value such as the annual revenue of a new restaurant based ...

Overview: Predictive models turn historical data into reliable forecasts that support accurate planning across ...

A hybrid modeling framework to optimize Chinese hamster ovary cell cultures for monoclonal antibody (mAb) production reduces the number of modeling parameters needed while returning results that ...

Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.