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 ...

The seemingly unpredictable, and thereby uncontrollable, dynamics of living organisms have perplexed and fascinated ...

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 ...

Highly reduced order models with nonlinear contact – extremely efficient computation. Modeled as linear components interconnected with highly reduced-order components. 1-linear reduced model, ...

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 ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...