Nonlinear mixed effects models (NLMMs) and self-modeling nonlinear regression (SEMOR) models are often used to fit repeated measures data. They use a common function shared by all subjects to model ...

This is a preview. Log in through your library . Abstract Multinomial logit models, especially those calibrated on scanner data, often use explanatory variables that are nonlinear functions of the ...

Author Dr. R. Russell Rhinehart discusses his new book, Nonlinear Model-Based Control: Using First-Principles Models in Process Control, and explains why nonlinear first-principles models should be ...

Given appropriate models for vacuum tubes, circuit simulators such as SPICE make analysis based on such nonlinear models a tractable effort. The Langmuir, Leach, and Koren models are discussed for the ...

Scientists are using an adapted version of VPIC, a particle-in-cell plasma physics code, to model the nonlinear physics of laser backscatter energy transfer and plasma instabilities in an attempt to ...

Materials scientists can learn a lot about a sample material by shooting lasers at it. With nonlinear optical microscopy—a specialized imaging technique that looks for a change in the color of intense ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

Researchers developed a nonlinear viscoelastic-plastic model to accurately forecast mining-induced subsidence, ensuring safer infrastructure construction.