Leo Spizzirri  does an excellent job of providing mathematical intuition behind eigenvector centrality. As I was reading through it, I found it easier to just work through the matrix operations he proposes using R.  You can find his paper her...

In a previous post, I described the basics of social network analysis. I plan to extend that example here with an application in predictive analytics. Let's suppose we have the following network (visualized in R)Suppose we have used the igraph package ...

In a previous post, I worked through the theory behind intervention analysis. In his time series course, University of Georgia political science professor Jamie Monogan demonstrates how to implement intervention analysis in R.  The following examp...

In a previous post I derived the least squares estimators using basic calculus, algebra, and arithmetic, and also showed how the same results can be achieved using the canned functions in SAS and R or via the matrix programming capabilities offered by ...

Regression Basicsy= b0 + b1 *X  ‘regression line we want to fit’The method of least squares minimizes the squared distance between the line ‘y’ andindividual data observations yi. That is minimize: ∑ ei2 = ∑ (yi - b0 -  b1 Xi...

In a previous post I discussed the concept of gradient descent.  Given some recent work in the online machine learning course offered at Stanford,  I'm going to extend that discussion with an actual example using R-code  (the actual code...

The following R code models a censored dependent variable (in this case academic aptitude) using a traditional least squares, tobit, and Bayesian approaches.  As depicted below, the OLS estimates (blue) for censored data are inconsistent and will ...

 posterior = (likelihood x prior) / integrated likelihoodThe combination of a prior distribution and a likelihood function is utilized to produce a posterior distribution.  Incorporating information from both the prior distribution and the likelihood function leads to a reduction in variance and an improved estimator. As n→ ∞ the likelihood centers over the ...

# ------------------------------------------------------------------ # |PROGRAM NAME: # |DATE: # |CREATED BY: MATT BOGARD # |PROJECT FILE: # |---------------------------------------------------------------- # | PURPOSE: ...