Monthly Archives: January 2014

Python and R: Is Python really faster than R?

January 30, 2014
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A friend of mine asked me to code the following in R:Generate samples of size 10 from Normal distribution with $\mu$ = 3 and $\sigma^2$ = 5;Compute the $\bar{x}$ and $\bar{x}\mp z_{\alpha/2}\displaystyle\frac{\sigma}{\sqrt{n}}$ using the 95% confidence...

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The Meta- State of the Union 2014

January 30, 2014
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The Meta- State of the Union 2014

Max Ghenis has a nice text analysis of Martin Luther King Jr.'s famous "I Have a Dream" speech. You can read about his methodology here:  Statistics meets rhetoric: A text analysis of "I Have a Dream" in R.This got me wondering about the President Obama's 2014 State of the Union speech. Using his template, you can see...

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Introduction to dplyr: data manipulation made easy(er) and fun(er)

January 30, 2014
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Introduction to dplyr: data manipulation made easy(er) and fun(er)

If you are just getting started in R, checkout my post on good references for beginners.  Hadly Wickham has come out with yet another R package that is destined to improve my workflow and let me concentrate less on getting R to do things, and more on my research questions. The package is dplyr, a reboot...

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More SOTU Scaling

January 30, 2014
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More SOTU Scaling

A couple of days ago the Monkey Cage featured Ben Lauderdale’s one-dimensional scaling model of US State of the Union addresses. In this post, I replicate the analysis with a closely related model, ask what the scaled dimension actually means, and consider what things would look like if we added another one. The technical details

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Inference for ARMA(p,q) Time Series

January 30, 2014
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Inference for ARMA(p,q) Time Series

As we mentioned in our previous post, as soon as we have a moving average part, inference becomes more complicated. Again, to illustrate, we do not need a two general model. Consider, here, some  process, where  is some white noise, and assume further that . > theta=.7 > phi=.5 > n=1000 > Z=rep(0,n) > set.seed(1) > e=rnorm(n) > for(t...

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Parallelizing #RStats using #make

January 30, 2014
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In the current post, I'll show how to use R as the main SHELL of GNU-Make instead of using a classical linux shell like 'bash'. Why would you do this ? awesomeness Make-based workflow management Make-based execution with --jobs. GNU make knows how to ...

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A First Look at rxDForest()

January 30, 2014
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A First Look at rxDForest()

by Joseph RIckert Last July, I blogged about rxDTree() the RevoScaleR function for building classification and regression trees on very large data sets. As I explaned then, this function is an implementation of the algorithm introduced by Ben-Haim and Yom-Tov in their 2010 paper that builds trees on histograms of data and not on the raw data itself. This...

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dplyr 0.1.1

January 30, 2014
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dplyr 0.1.1

We’re pleased to announce a new minor version of dplyr. This fixes a few bugs that crashed R, adds a few minor new features (like a sort argument to tally()), and uses shallow copying in a few more places. There is one backward incompatible change: explain_tbl() has been renamed to explain. For a complete list

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roxygen2 3.1.0

January 30, 2014
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roxygen2 3.1.0

We’re pleased to announce a new version of roxygen2. The biggest news is that roxygen2 now recognises reference class method docstrings and will automatically add them to the documentation. 3.1.0 also offers a number of minor improvements and bug fixes, as listed on the github release notice. As always, you can install the latest version with install.packages("roxygen2").

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R for spatial analysis tutorial + video

January 30, 2014
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On 24th January 2014 I ran a one day practical course on an "Introduction to Spatial Data Visualisation in R" at the University of Leeds, with the help of demonstrators Rachel Oldroyd and Alistair Leak, who came up from London for the event. The course is designed for people completely new to R, who are especially interested in its spatial...

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