Researchers used a process called symbolic regression to derive the equations from a biogeochemical model of the ocean.

Current metabolic modeling tools suffer from a variety of limitations, from scalability to simplifying assumptions, that preclude their use in many applications. We recently created a modeling ...

Learn how nonlinear and linear regression models differ, predict variables, and their applications in data analysis for accurate results.

Linear superposition, as its name implies, is associated with linear systems. In your core undergraduate electrical circuits class, you learned that networks comprising only resistors, capacitors and ...

Structural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis of variance ...

Partial differential equations (PDEs) are ubiquitous in natural science and engineering problems. Traditional discrete methods for solving PDEs are usually time-consuming and labor-intensive due to ...

Sometimes ecological data just don’t make sense. The sockeye salmon that spawn in British Columbia’s Fraser River offer a prime example. Scientists have tracked the fishery there since 1948, through ...