892 search results for "how to import image file to R"

DC R Meetup: “Analyze US Government Survey Data with R”

January 10, 2013
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DC R Meetup: “Analyze US Government Survey Data with R”

I really enjoyed tonight’s DC R Meetup, presented by the prolific Anthony Damico. I’ve met Anthony before to discuss whether the Census Bureau could either… publish R-readable … Continue reading →

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R for actuarial science

January 10, 2013
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R for actuarial science

As mentioned in the Appendix of Modern Actuarial Risk Theory, “R (and S) is the ‘lingua franca’ of data analysis and statistical computing, used in academia, climate research, computer science, bioinformatics, pharmaceutical industry, customer analytics, data mining, finance and by some insurers. Apart from being stable, fast, always up-to-date and very versatile, the chief advantage of R is that...

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Monotonic deshrinking in weighted averaging models

January 5, 2013
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Monotonic deshrinking in weighted averaging models

Weighted averaging regression and calibration is the most widely used method for developing a palaeolimnological transfer function. Such models are used to reconstruct properties of the past lake environment such as pH, total phosphorus, and water temperature with, it has … Continue reading →

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Multiple Classification and Authorship of the Hebrew Bible

January 1, 2013
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Multiple Classification and Authorship of the Hebrew Bible

Sitting in my synagogue this past Saturday, I started thinking about the authorship analysis that I did using function word counts from texts authored by Shakespeare, Austen, etc.  I started to wonder if I could do something similar with the … Continue reading →

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Anaerobic Stress in Seeds – A Chemical Similarity Network Story

December 31, 2012
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Anaerobic Stress in Seeds – A Chemical Similarity Network Story

The chemical similarity network or CSN is a great tool for organizing biological data based on known biochemistry or chemical structural similarity. Here is an example CSN for visualizing metabolomic  changes (measured via GC/TOF) due to anaerobic stress in germinating seeds. In this network edges are formed for chemical similarity scores > 75. Node color describes

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Integration of R, RStudio and Hadoop in a VirtualBox Cloudera Demo VM on Mac OS X

December 29, 2012
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Integration of R, RStudio and Hadoop in a VirtualBox Cloudera Demo VM on Mac OS X

MotivationI was inspired by Revolution's blog and step-by-step tutorial from Jeffrey Breen on the set up of a local virtual instance of Hadoop with R. However, this tutorial describes the implementation using VMware's application. One downside to using VMware is that it's not free. I know most of the people including me like to hear the words open-source and free,...

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Row-wise summary curves in faceted ggplot2 figures

December 29, 2012
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Row-wise summary curves in faceted ggplot2 figures

I really enjoy reading the Junk Charts blog.  A recent post made me wonder how easy it would be to add summary curves for small-multiple type plots, assuming the “small multiples” to summarize were the X component of a ggplot2::facet_grid(Y ~ X) … Continue reading →

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UEFA, what were the odds ?

December 27, 2012
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UEFA, what were the odds ?

Ok, I was supposed to take a break, but Frédéric, professor in Tours, came back to me this morning with a tickling question. He asked me what were the odds that the Champions League draw produces exactly the same pairings from the practice draw, and the official one (see e.g. dailymail.co.uk/…). To be honest, I don’t know much about soccer, so...

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My Intro to Multiple Classification with Random Forests, Conditional Inference Trees, and Linear Discriminant Analysis

December 27, 2012
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My Intro to Multiple Classification with Random Forests, Conditional Inference Trees, and Linear Discriminant Analysis

After the work I did for my last post, I wanted to practice doing multiple classification.  I first thought of using the famous iris dataset, but felt that was a little boring.  Ideally, I wanted to look for a practice … Continue reading →

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Binary Classification – A Comparison of “Titanic” Proportions Between Logistic Regression, Random Forests, and Conditional Trees

December 23, 2012
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Binary Classification – A Comparison of “Titanic” Proportions Between Logistic Regression, Random Forests, and Conditional Trees

Now that I’m on my winter break, I’ve been taking a little bit of time to read up on some modelling techniques that I’ve never used before. Two such techniques are Random Forests and Conditional Trees.  Since both can be used … Continue reading →

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