highlight 0.4.1

April 10, 2013
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The highlight package has been missing from CRAN for quite some time Now it is back, with fewer dependencies. It used to depend on Rcpp and parser, but since the code logic from parser has been brought to R, highlight … Continue reading →

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Mobile version of the graph gallery

April 10, 2013
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Mobile version of the graph gallery

The R Graph Gallery has been a popular website for many years now. The number of graphics keeps growing as people send me their code. When browsing the website with a mobile device the experience was frustrating, as too much … Continue reading →

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Milano (Italy). April 18, 2013. Third Milano R net meeting: agenda

April 10, 2013
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Milano (Italy). April 18, 2013. Third Milano R net meeting: agenda

April 18, 2013 - 18:00 - 21:00 Fiori Oscuri Bistrot & Bar (www.fiorioscuri.it) Via Fiori Oscuri, 3 - Milano (Zona Brera) 18.00 - 18.15 Registration 18.15 - 18.30 Welcome presentation Andrea Spanò, Partner at Quantide 18.30 - 19.00 Digit recognition Machine … Continue reading →

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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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Gradient Boosting: Analysis of LendingClub’s Data

April 8, 2013
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Gradient Boosting: Analysis of LendingClub’s Data

An old 5.75% CD of mine recently matured and seeing that those interest rates are gone forever, I figured I’d take a statistical look at LendingClub’s data. Lending Club is the first peer-to-peer lending company to register its offerings as securities with the Securities and Exchange Commission (SEC). Their operational statistics are public and available for download. The latest

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Knoxville R Users Group Formed, Free Training Offered

April 8, 2013
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Knoxville R Users Group Formed, Free Training Offered

R is popular free and open-source software for graphics and data analytics. The Knoxville R Users Group is being formed to help people learn R and improve their skills with it. Three departments of The University of Tennessee are working together … Continue reading →

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Package-Wide Variables/Cache in R Packages

April 8, 2013
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It’s often beneficial to have a variable shared between all the functions in an R package. One obvious example would be the maintenance of a package-wide cache for all of your functions. I’ve encountered this situation multiple times and always forget at least one important step in the process, so I thought I’d document it

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painful truncnorm

April 8, 2013
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painful truncnorm

As I wanted to simulate truncated normals in a hurry, I coded the inverse cdf approach: instead of using my own accept-reject algorithm. Poor shortcut as the method fails when a and b are too far from μ So I introduced a control (and ended up wasting more time than if I had used my

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Instructions for Installing & Using R on Amazon EC2

April 8, 2013
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If you’re an R user, you’ve surely heard all the hype around ‘big data’ and how R is commonly used to analyze these volumes of data. One thing that’s often missing from the discussion is HOW to work around issues using big data and R, specifically how to deal with the fact that R stores Instructions for Installing...

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Use foursquare to locate a twitter user using R

April 8, 2013
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Use foursquare to locate a twitter user using R

I've been doing some work with Twitter data. In much of this work, my life would be so much easier if we could geographically locate the origin of the tweets. There are some ways to do this using the twitter APIs. For example, if a user has geo-locatio...

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Visualize large data sets with the bigvis package

April 8, 2013
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Visualize large data sets with the bigvis package

Creating visualizations of large data sets is a tough problem: with a limited number of pixels available on the screen (or just with the limited visual acuity of the human eye), massive numbers of symbols on the page can easily result in an uninterpretable mess. On Friday we shared one way of tackling the problem using Revolution R Enterprise:...

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Halo Effects vs. Intention-Laden Ratings: Separating Baby and Bathwater

April 8, 2013
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Halo Effects vs. Intention-Laden Ratings: Separating Baby and Bathwater

Are halo effects real or illusory?  Much has been written arguing that rating scales contain extensive amounts of measurement bias.  Some tells us to avoid ratings altogether (What do customers really want?).  Others warn against the use of ratings scales without major adjustments (e.g., overcoming scale usage heterogeneity with the R package bayesm).  Obviously, by including the...

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More variables, spinoff projects, and RuPaul’s Drag Race season 5 predictions: episode 10

April 8, 2013
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More variables, spinoff projects, and RuPaul’s Drag Race season 5 predictions: episode 10

Last week, Alyssa got the boot and Jinkx kept her place. And I totally called it with my first model that accounted for the proportional hazards assumption. I think the model is having a little more success as the season plods on. Before I get to the predictions for episode 10, there’s two really interesting… Continue reading →

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Spring Cleaning Data: 1of 6- Downloading the Data & Opening Excel Files

April 8, 2013
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With spring in the air, I thought it would be fun to do a series on (spring) cleaning data. The posts will follow my efforts to to download the data, import into R, cleaned it up, merge the different files, add columns of information created, and then ...

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Starting Analysis and Visualisation of Spatial Data with R

April 8, 2013
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Starting Analysis and Visualisation of Spatial Data with R

Last week I ran an introductory workshop on the analysi

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Dynamic Wrapping and Recursion with Rcpp

April 8, 2013
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Dynamic Wrapping and Recursion with Rcpp

We can leverage small parts of the R’s C API in order to infer the type of objects directly at the run-time of a function call, and use this information to dynamically wrap objects as needed. We’ll also present an example of recursing through a list. To get a basic familiarity with the main functions exported from R API, I...

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Dynamic Wrapping and Recursion with Rcpp

April 8, 2013
By
Dynamic Wrapping and Recursion with Rcpp

We can leverage small parts of the R’s C API in order to infer the type of objects directly at the run-time of a function call, and use this information to dynamically wrap objects as needed. We’ll also present an example of recursing through a list. To get a basic familiarity with the main functions exported from R API, I...

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Next Kölner R User Meeting: 12 April 2013

April 8, 2013
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Next Kölner R User Meeting: 12 April 2013

Quick reminder: The next Cologne R user group meeting is scheduled for this Friday, 12 April 2013. We will discuss cluster analysis and shiny. Further details and the agenda are available on our KölnRUG Meetup site. Please sign up if you would like to come along. Notes from the last Cologne R user group meeting are...

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analyze the pesquisa nacional por amostra de domicilios (pnad) with r

April 7, 2013
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think of the pesquisa nacional por amostra de domicilios (pnad) as the brazilian census for off-years - the ones that don't end in zero.  the principal household survey for the nation of brazil, pnad measures general education, labor, income, and ...

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Dirichlet Process, Infinite Mixture Models, and Clustering

April 7, 2013
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Dirichlet Process, Infinite Mixture Models, and Clustering

The Dirichlet process provides a very interesting approach to understand group assignments and models for clustering effects.   Often time we encounter the k-means approach.  However, it is necessary to have a fixed number of clusters.  Often we encounter situations where we don’t know how many fixed clusters we need.  Suppose we’re trying to identify

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