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 ...
Bayesian methods for dynamic models in marketing have so far been parametric. For instance, it is invariably assumed that model errors emerge from normal distributions. Yet using arbitrary ...
Researchers developed a nonlinear viscoelastic-plastic model to accurately forecast mining-induced subsidence, ensuring safer ...
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 ...
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Optical system uses diffractive processors to achieve large-scale nonlinear computation
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 ...
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