Model fit can be assessed using the difference between the model's predictions and new data (prediction error—our focus this month) or between the estimated and ...

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.

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

When working with applications in ASP.NET Core 6 you will often want to validate your models to ensure that the data they contain conform to the pre-defined validation rules. Enter model validation.