Overview Regression explains how changes in one factor influence another with clarity.Each regression type is suited for ...

Model building via linear regression models. Method of least squares, theory and practice. Checking for adequacy of a model, examination of residuals, checking outliers. Practical hand on experience ...

Now that you've got a good sense of how to "speak" R, let's use it with linear regression to make distinctive predictions. The R system has three components: a scripting language, an interactive ...

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 ...

Dr. James McCaffrey of Microsoft Research uses code samples, a full C# program and screenshots to detail the ins and outs of kernal logistic regression, a machine learning technique that extends ...

The efficiency gain of seemingly unrelated regression (SUR) relative to OLS is a decreasing function of correlation of variables across equations. This article examines the efficiency gain for an ...

Partial least squares structural equation modeling (PLS-SEM) has become a key method in international marketing research. Users of PLS-SEM have, however, largely overlooked the issue of endogeneity, ...

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...