# Monthly Archives: August 2009

## R handy for crunching data

August 23, 2009
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http://www.ibm.com/developerworks/library/l-sc16.html?S_TACT=105AGX52&S_CMP=cn-a-l

August 22, 2009
By

For those who are scared of Emacs: http://sourceforge.net/projects/npptor/

## Test cointegration with R

Cointegrated pairs of securities are crucial for mean reversion trading portfolio construction, Play with cointegration has several good papers to start with. Should you want to test pairs of securities for cointegration using R, here is an excellent ...

## No success yet, then more animations…

August 20, 2009
By

So I've been here dealing with the installation of a software that Yihui Xie suggested me to change the format of the animations displayed in R, she told me that all I needed to do was to go to http://imagemagick.org to download ImageMagick for my ope...

## No success yet, then more animations…

August 20, 2009
By

So I've been here dealing with the installation of a software that Yihui Xie suggested me to change the format of the animations displayed in R, she told me that all I needed to do was to go to http://imagemagick.org to download ImageMagick for my ope...

## Simple logistic regression on qualitative dichotomic variables

August 20, 2009
By

In this post we will see briefly how to implement a logistic regression model if you have categorical variables, or qualitative, organized in double entry contingency tables. In this model the dependent variable (Y) and independent variable (X) are both dichotomies (or Bernoullian).In general, the probability that Y = 1 as a function of predictors is:$$P(Y=1|X=x)=\pi(x)=\frac{exp(\beta_0+\beta_1x_1+\cdots +\beta_kx_k)}{1+exp(\beta_0+\beta_1x_1+\cdots +\beta_kx_k)}$$Our goal...

## Simple logistic regression on qualitative dichotomic variables

August 20, 2009
By

In this post we will see briefly how to implement a logistic regression model if you have categorical variables, or qualitative, organized in double entry contingency tables. In this model the dependent variable (Y) and independent variable (X) are both dichotomies (or Bernoullian).In general, the probability that Y = 1 as a function of predictors is:$$P(Y=1|X=x)=\pi(x)=\frac{exp(\beta_0+\beta_1x_1+\cdots +\beta_kx_k)}{1+exp(\beta_0+\beta_1x_1+\cdots +\beta_kx_k)}$$Our goal...

## ggplot2 Version of Figures in “Lattice: Multivariate Data Visualization with R” (Part 13)

August 20, 2009
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This is the 13th post in a series attempting to recreate the figures in Lattice: Multivariate Data Visualization with R (R code available here) with ggplot2. Previous parts in this series: Part 1, Part 2, Part 3, Part 4, Part 5, Part 6, Part 7, Part 8, Part 9, Part 10, Part 11, Part 12.Chapter 14

## 2 Interesting animations…

August 19, 2009
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So I haven't had success YET in finding a way to post here the animations, but I thought it would be interesting to show you at least a couple of examples using this software, and I chose 2 pretty interesting ones by Yihui Xie and Xiaoyue Cheng.The fir...