Updates to the Social Science Starter Kit

May 27, 2013
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The Emacs Social Science Starter Kit is a drop-in collection of packages and settings for Emacs 24 aimed at people like me: that is, people doing social science data analysis and writing, using some combination of tools like R, git, LaTeX, Pandoc, perh...

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Writing a Minimal Working Example (MWE) in R

May 27, 2013
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Writing a Minimal Working Example (MWE) in R

How to Ask for Help using R How to Ask for Help using R The key to getting good help with an R problem is to provide a minimally working reproducible example (MWRE). Making an MWRE is really easy with R, and it will help ensure that...

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Bayesian model II regression

May 27, 2013
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Bayesian model II regression

Regression is a mainstay of ecological and evolutionary data analysis. For example, a disease ecologist may use body size (e.g. a weight from a scale with measurement error) to predict infection. Classical linear regression assumes no error in covariates; they are known exactly. This is rarely the case in ecology, and ignoring error in covariates can bias regression coefficient...

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(Another) introduction to R

May 27, 2013
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(Another) introduction to R

It’s Memorial Day and my dissertation defense is tomorrow. This week I’m phoning in my blog. I had the opportunity to teach a short course last week that was part of a larger workshop focused on ecosystem restoration. A fellow grad student and I taught a session on Excel and R for basic data analysis.

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useR! 2013 conference update

May 27, 2013
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Been trying to reach the website for the useR! 2013, the R user conference that will be held July 10-12 2013 at University of Castilla-La Mancha in Spain? There have been some server problems recently, but you can now get access at the official URL, www.r-project.org/useR-2013/. If you're going, be sure to check out the newly-announced Data Analysis Contest,...

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Log Transformations for Skewed and Wide Distributions

May 27, 2013
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Log Transformations for Skewed and Wide Distributions

This is a guest article by Nina Zumel and John Mount, authors of the new book Practical Data Science with R. For readers of this blog, there is a 50% discount off the “Practical Data Science with R” book, simply by using the code pdswrblo when reaching checkout (until …Read more »

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Permutation optimization with gaoptim package

May 27, 2013
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My recent update of gaoptim package brings up a new function, GAPerm, which can be used to perform combinatorial optimization using the Genetic Algorithm approach. The example below solves a TSP instance with 10 points around a circumference, the...

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Combinatorial optimization with gaoptim package

May 27, 2013
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My recent update of gaoptim package brings up a new function, GAPerm, which can be used to perform combinatorial optimization using the Genetic Algorithm approach. The example below solves a TSP instance with 10 points around a circumference, the...

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R / Finance 2013 Recap — and Presentation Slides

The fifth internation R/Finance conference was held last weekend. As one of the founding co-organizers, I may well be accussed of a little bias, but we think we once again pulled off a very nice and successful weekend-long event. Participants had ki...

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Creating a presence-absence raster from point data

May 27, 2013
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Creating a presence-absence raster from point data

I’m working on generating species distribution models at the moment for a few hundred species. Which means that I’m trying to automate as many steps as possible in R to avoid having to click buttons hundreds of times in ArcView. … Continue reading →

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BISON USGS species occurrence data

May 27, 2013
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BISON USGS species occurrence data

The USGS recently released a way to search for and get species occurrence records for the USA. The service is called BISON (Biodiversity Information Serving Our Nation). The service has a web interface for human interaction in a browser, and two APIs (application programming interface) to allow machines to interact with their database. One of the...

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Import All Text Files in A Folder with Parallel Execution

May 26, 2013
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Import All Text Files in A Folder with Parallel Execution

Sometimes, we might need to import all files, e.g. *.txt, with the same data layout in a folder without knowing each file name and then combine all pieces together. With the old method, we can use lapply() and do.call() functions to accomplish the task. However, when there are a large number of such files and

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Logging Data in R Loops: Applied to Twitter.

May 26, 2013
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A problem that many users face in R is storing the output from loop operations. In the case of Twitter, we may be requesting the last specified number of Tweets from a number of Twitter users. Several methods exist for … Continue reading →

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Pairwise distances in R

May 26, 2013
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Pairwise distances in R

For a recent project I needed to calculate the pairwise distances of a set of observations to a set of cluster centers. In MATLAB you can use the pdist function for this. As far as I know, there is no equivalent in the R standard packages. So I looked into writing a fast implementation for

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Exploratory Data Analysis: Variations of Box Plots in R for Ozone Concentrations in New York City and Ozonopolis

Exploratory Data Analysis: Variations of Box Plots in R for Ozone Concentrations in New York City and Ozonopolis

Introduction Last week, I wrote the first post in a series on exploratory data analysis (EDA).  I began by calculating summary statistics on a univariate data set of ozone concentration in New York City in the built-in data set “airquality” in R.  In particular, I talked about how to calculate those statistics when the data

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Using R to visualize geo optimization algorithms

May 26, 2013
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Using R to visualize geo optimization algorithms

Site optimization is the process of finding an optimal location for a plant or a warehouse to minimize transportation costs and duration. A simple model only consists of one good and no restrictions regarding transportation capacities or delivery time. The optimizing algorithms are often hard to understand. Fortunately, R is a great tool to make them more comprehensible.The basic...

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Creating a typical textbook illustration of statistical power using either ggplot or base graphics

May 26, 2013
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Creating a typical textbook illustration of statistical power using either ggplot or base graphics

A common way of illustrating the idea behind statistical power in null hypothesis significance testing, is by plotting the sampling distributions of the null hypothesis and the alternative hypothesis. Typically, these illustrations highlight the regions that correspond to making a type II error, type I error and correctly rejecting the null hypothesis (i.e. the test's power). In this post...

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More bubble sort tuning

May 26, 2013
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After last week's post bubble sort tuning I got an email from Berend Hasselman noting that my 'best' function did not protect against cases n<=2 and a speed improvement was possible. That made me realize that I should have been profiling t...

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Test Drive of Parallel Computing with R

May 25, 2013
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Test Drive of Parallel Computing with R

Today, I did a test run of parallel computing with snow and multicore packages in R and compared the parallelism with the single-thread lapply() function. In the test code below, a data.frame with 20M rows is simulated in a Ubuntu VM with 8-core CPU and 10-G memory. As the baseline, lapply() function is employed to

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Revisiting text processing with R and Python

May 25, 2013
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  Back in 2011, I covered the relative performance difference of the most popular libraries for text processing in R and Python.   In case you can’t guess the answer, Python and NLTK  won by a significant margin over R and… Read more ›

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Speed trick: Assigning large object NULL is much faster than using rm()!

May 25, 2013
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When processing large data sets in R you often also end up creating large temporary objects. In order to keep the memory footprint small, it is always good to remove those temporary objects as soon as possible. When done, removed objects will be deallocated from memory (RAM) the next time the garbage collection runs. Better: Use rm(list="x")...

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HOWTO: X11 Forwarding for Oracle R Enterprise

May 25, 2013
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HOWTO: X11 Forwarding for Oracle R Enterprise

v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false EN-US X-NONE X-NONE ...

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Sentiment analysis finds trouble in the Enron emails

May 24, 2013
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Sentiment analysis finds trouble in the Enron emails

The Enron email dataset, collected during the FERC investigation of the Enron financial scandal, represents the largest publicly available set of emails. This makes theman ideal testbed for sentiment analysis algorithms. Ikanow's Andrew Strite used the open-source Infinit.e framework and a Hadoop cluster to generate sentiment scores for all of the Enron emails, and then used R to manipulate...

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Down and Dirty Forecasting: Part 2

May 24, 2013
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Down and Dirty Forecasting: Part 2

This is the second part of the forecasting exercise, where I am looking at a multiple regression. To keep it simple I chose the states that boarder WI and the US unemployment information for the regression. Again this is a down and dirty analysis, I wo...

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What is probabilistic truth? Part 2 – Everything is conditional

May 24, 2013
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What is probabilistic truth? Part 2 – Everything is conditional

Read Part 1 When making a statement of the form “1/2 is the correct probability that this coin will land tails”, there are a few things which are left unsaid, but which are typically implied. The statement is one about the probability of an unknown event occurring, and it would seem reasonable to write this

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Down and Dirty Forecasting: Part 1

May 24, 2013
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Down and Dirty Forecasting: Part 1

I wanted to see what I could do in a hurry using the commands found at Forecasting: Principles and Practice . I chose a simple enough data set of Wisconsin Unemployment from 1976 to the present (April 2013). I kept the last 12 months worth of...

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Compiling R from Source with OpenMP, Accelerate and MKL in OS X

May 24, 2013
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Compiling R from Source in OS X I set out to find out whether I could speed up R by compiling it from source and: using Apple´s Accelerate Framework enabling OpenMP (which is disabled under OS X and Windows by default, but enabled under Linux) using Intel´s Intel´s Math Kernel Library I also wanted to know how an implicit parallel library,...

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Shiny + Concerto = YES !!!

May 23, 2013
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Shiny + Concerto = YES !!!

So I have finally gotten beta access to the two most powerful R controlled web application makers in existence and produced very exciting experimental productsA few posts ago I posted a Visual Reasoning Test that I had made by hand and powered wit...

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Robert Hijmans on Spatial Data Analysis

May 23, 2013
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Last week at the Davis R Users’ Group Robert Hijmans gave a talk about spatial data analysis in R. Robert is a professor of biogeography at UC Davis and the author of the raster (analysis of gridded data), dismo (species distribution modeling), and geosphere (spherical trigonometry), packages. Robert’s presentation spanned topics including basic...

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