The class of nonlinear stochastic regression models includes most of the linear and nonlinear models used in time series, stochastic control and stochastic approximation schemes. The consistency of ...

Choong Nyoung Kim and Raymond McLeod, Jr. Analysis of human judgment and decision making provides useful methodologies for examining the human decision process and substantive results. One such ...

Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...

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

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive ...