Monthly Archives: April 2013

Finding the Distribution Parameters

April 9, 2013
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Finding the Distribution Parameters

This is a brief description on one way to determine the distribution of given data. There are several ways to accomplish this in R especially if one is trying to determine if the data comes from a normal distribution. Rather than focusing on hypothesis testing and determining if a distribution is actually the said distribution

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2013-4 Generating Structured and Labelled SVG

April 9, 2013
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This article discusses the importance of providing structure and labelling within SVG code, particularly when the SVG code is generated indirectly by a high-level system and when the SVG code describes a complex image such as a statistical plot. We … Continue reading →

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Second edition of Crawley’s The R Book

April 9, 2013
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Second edition of Crawley’s The R Book

The second edition of Michael Cawley's The R Book is available from Wiley. According to the publisher, the new edition boasts the following features:"Features full colour text and extensive graphics throughout.Introduces a clear structure with numbered...

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Some R User Group Presentations from Europe

April 9, 2013
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by Joseph Rickert I am beginning to get excited about going to Spain for useR 2013 which will be held at the University of Castilla-La Mancha, so I have been using the links on the Revolution's local user directory webpage to see what the European R user groups are doing. Here are just a few highlights of materials that...

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Behind the NCAA Visualizer: Python, R and JavaScript

April 9, 2013
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Rodrigo Zamith's NCAA Tournament Visualizer is a great example of an interactive data visualization. If you want to create something similar, Rodrigo has shared detailed behind-the-scenes information on how it was created. He used a mix of tools: Python was used to scrape team statistics fromt the NCAA website R was used to prepare the data for analysis, and...

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Matrix Cumulative Coherence: Fourier Bases, Random and Sensing Matrices

April 9, 2013
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Compressive sampling (CS) is revolutionizing the way we process analog to digital conversion, our understanding of linear systems and the limits of information theory. One of the key concept in CS is that a signal can be represented in a sparse bases o...

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Spring Cleaning Data: 2 of 6- Changing Column Names and Adding a Column

April 9, 2013
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The first post (found here) we downloaded the data and imported it to R using the gdata package. This post we will be changing the column names to make them more reasonable, and adding a quarter variable. The reason for changing the column names is bec...

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Happy biRthday

April 9, 2013
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Happy biRthday

Today is my birthday. It’s also the birthday of a close friend. What an incredible coincidence! Or wait, may be is just expected. One more time R comes into our help, because it has a built-in function to answer our question. … Continue reading →

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How to set axis options in googleVis

April 9, 2013
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How to set axis options in googleVis

Setting axis options in googleVis charts can be a bit tricky. Here I present two examples where I set several options to customise the layout of a line and combo chart with two axes. The parameters have to be set in line with the Google Chart Tools API, which uses a JavaScript syntax....

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Changing figure options mid-chunk (in a loop) using the pander package.

April 9, 2013
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Changing figure options mid-chunk (in a loop) using the pander package.

I wrote already about changing figure options mid-chunk in reproducible research. This can be important  e.g. if you are looping through a dataset to produce a graphic for each variable but the figure width or height need to depend on properties of the variables, e.g. if you are producing histograms and want the figures to

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