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 ...

Materials scientists can learn a lot about a sample material by shooting lasers at it. With nonlinear optical microscopy—a ...

This article reviews work on the planning of experiments with response functions nonlinear in some parameters. Apart from older work on dilution series experiments and quantal bioassays, this field is ...

We leverage recent advancements in machine learning to develop an integrated method to solve globally and estimate models featuring agent heterogeneity, nonlinear constraints, and aggregate ...

From industrial robots to self-driving cars, engineers face a common problem: keeping machines steady and predictable. When ...

The study departs from conventional mean-based economic forecasting by focusing on quantile prediction, a technique that ...

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 ...

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 ...

University of Queensland researchers have created a microscopic "ocean" on a silicon chip to miniaturize the study of wave ...