Monthly Archives: September 2014

Complex Domain Coloring

September 30, 2014
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Complex Domain Coloring

Why don’t you stop doodling and start writing serious posts in your blog? (Cecilia, my beautiful wife) Choose a function, apply it to a set of complex numbers, paint  the result using the HSV technique and be ready to be impressed because images can be absolutely amazing. You only need ggplot2 package and your imagination. This is what happens

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Implementing an EM Algorithm for Probit Regressions

September 30, 2014
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Implementing an EM Algorithm for Probit Regressions

Users new to the Rcpp family of functionality are often impressed with the performance gains that can be realized, but struggle to see how to approach their own computational problems. Many of the most impressive performance gains are demonstrated with seemingly advanced statistical methods, advanced C++–related constructs, or both. Even when users are able to understand how various demonstrated features operate in isolation, examples...

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Structured simulation of regression models – simReg package.

September 30, 2014
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I'd like to introduce a package that simulates regression models. This includes both single level and multilevel (i.e. hierarchical or linear mixed) models up to two levels of nesting. The package produces a unified framework to simulate all types of c...

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Install R in Android, via GNURoot -no root required!

September 30, 2014
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Install R in Android, via GNURoot -no root required!

Playing with my tablet some time ago, I wondered if installing R could be possible. You know, a small android device “to the power of R”… After searching on Google from time to time, I came across some interesting possibilities: … Sigue leyendo →

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Interactive Visualisation of the Profitable Amount of Waste to Dispose Illegally

September 30, 2014
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Interactive Visualisation of the Profitable Amount of Waste to Dispose Illegally

"Wow!" - I said to myself after reading R Helps With Employee Churn post - "I can create interactive plots in R?!!! I have to try it out!" I quickly came up with an idea of creating interactive plot for my simple model for assessment of the profitable ratio between the volume waste that could be illegally...

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Generating Hurricanes with a Markov Spatial Process

September 30, 2014
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Generating Hurricanes with a Markov Spatial Process

The National Hurricane Center (NHC) collects datasets with all  storms in North Atlantic, the North Atlantic Hurricane Database (HURDAT). For all sorms, we have the location of the storm, every six jours (at midnight, six a.m., noon and six p.m.). Note that we have also the date, the maximal wind speed – on a 6 hour window – and...

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Meet us at R Day and at the Strata+Hadoop World NYC Oct 15-17, 2014

September 30, 2014
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Meet us at R Day and at the Strata+Hadoop World NYC Oct 15-17, 2014

Are you headed to Strata? It’s just around the corner! We particularly hope to see you at R Day on October 15, where we will cover a raft of current topics that analysts and R users need to pay attention to. The R Day tutorials come from Hadley Wickham, Winston Chang, Garrett Grolemund, J.J. Allaire, and

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Additional tips for structuring an individual-based model in R

September 30, 2014
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Additional tips for structuring an individual-based model in R

 I had a reader ask me recently to help understand how to modify the code of an individual-based model (IBM) that I posted a while back. It was my first attempt at an IBM in R, and I realized that I have made some significant changes to the way th...

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Why are we still teaching T-tests?

September 30, 2014
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The following post by Norm Matloff originally appeared on his blog, Mad(Data)Scientist, on September 15th. We rarely republish posts that have appeared on other blogs, however, the questions that Norm raises both with respect to the teaching of statistics, and his assertion that "R's statistical procedures are centered far too much on significance testing" deserve a second look. Moreover,...

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Building a DGA Classifier: Part 1, Data Preparation

September 30, 2014
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This will be a three-part blog series on building a DGA classifier and will be split into three logical phases of building a classifier: 1) Data preparation (this) 2) Feature engineering and 3) Model selection. And before I get too far into this, I want to give a huge thank you to Click Security for releasing a DGA classifier in python as part of...

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