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 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: ...

My thirst for statistics has been increasing. IV had another requirement, which would eventually be useful to me as well. He currently downloads FII and DII buy and sell values and its impact on Nifty manually in Excel. He suggested me to try and autom...

One of my TI forum members IV had a requirement for BSE Quotes along with Delivery Quantity. This made me implement "merge" function of R coding (thanks to the great work done by people behind various packages and guidance available on R Mailing lists)...

Earlier, I had worked around to download Bhavcopy from NSE. Now, I would make a similar attempt to download the BSE BhavcopyObjective: Download Bhavcopy (Equity) from http://www.bseindia.com and save only relevant columns Date, Symbol, Name, Open, High...

My prime interest being the Indian financial markets, the first step would be to get the data to play around. NSE India provides EOD of data as bhavcopies. The same are stored as zipped files at their servers. Downloading them one by one for a larger t...

The SAS Analysis blog post 'A macro calls R in SAS for paneled 3d plotting' influenced my macro coding.   The following macro call: %EXPORT_TO_R(DATA = YOURDATA)  exports the SAS data set 'YOURDATA' as .csv and produces the R code for se...

I developed the following schematic (with annotations) based on supporting documents (link) from the article cited below. The authors used R for their work. The ROC curve in my schematic was output from PROC LOGISTIC in SAS, the scatterplot with m...