Recognizing the nonlinear behavior of the 12AX7 vacuum tube, used in audio and old op-amp applications, Dr. Dyer compares various models for fit to real-world device data.

Fast neural network techniques—extreme learning machine and radial basis function networks—are used to solve the traditional curve fitting problems, where the localized effect of a network basis ...

Evaluating the performance of non-linear regression models is crucial in data analytics. It's about understanding how well your model fits the data you're analyzing. This fit determines the model ...

Prism is a popular curve fitting software developed by GraphPad. This tool combines scientific graphing, comprehensive curve fitting, statistics, and data organization. Prism is a tool used mainly by ...

Nonlinear regression uses logarithmic functions, trigonometric functions, exponential functions, power functions, Lorenz curves, Gaussian functions, and other fitting methods.

Inflation has climbed since 2021, as the labor market has tightened. Two historical data relationships can account for elevated inflation over the past two years: the Beveridge curve, which relates ...

The lmfit Python library provides tools for non-linear least-squares minimization and curve fitting. The goal is to make these optimization algorithms more flexible, more comprehensible, and easier to ...