Climate and ocean models use a series of equations to represent complex natural processes. However, the equations used in ...

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

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 ...

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 ...

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 ...

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 ...

Microbiome sequencing data are known to be biased; the measured taxa relative abundances can be systematically distorted from their true values at every step in the experimental/analysis workflow. If ...

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 ...

Part one of this series, published in the January 2007 issue, discussed how to use linear superposition in the steady-state analysis of multiple heat-source systems. However, linear superposition also ...