This technical FAQ examines three modeling gaps identified in engineering literature and outlines algorithmic methods to address them.

In risk analysis, researchers often fit many candidate distributions to frequency and severity data and select based on goodness-of-fit. In a new study published in Risk Sciences, the authors ...

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, ...

A variety of linear models are available to represent common active electronic devices such as transistors and vacuum tubes. Devices operating under large-signal conditions often require nonlinear ...