Monthly Archives: March 2014

Bayesian Data Analysis [BDA3]

March 27, 2014
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Bayesian Data Analysis [BDA3]

Andrew Gelman and his coauthors, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Don Rubin, have now published the latest edition of their book Bayesian Data Analysis. David and Aki are newcomers to the authors’ list, with an extended section on non-linear and non-parametric models. I have been asked by Sam Behseta to write

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Assign n Email Addresses to x Cells, Intrinsically (Part II)

March 27, 2014
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Part I showed the concept and general technique of a method of assigning n email addresses to x cells pseudo-randomly, without the need for maintaining a log of each assignment.The earlier post considered the basic case of each cell being assigned approximately the same quantity of email addresses. In practice, cell sizes often vary. Below is a technique that...

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Analysis of experiments using ASReml-R, Chicago, 24/25th April

March 27, 2014
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This workshop is aimed at scientist/practitioners that are interested in analyzing complex datasets by fitting linear mixed models, particularly users with experience in breeding programs and design and analysis of experiments. After the workshop the participants should be able to understand the use of ASReml and to analyze most biological experiment and particularly, study breeding trials for single or...

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Data Preparation – Part II

March 27, 2014
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Data Preparation – Part II

This time i will talk about how to deal with large text files in chuncks with R. Just to provide The post Data Preparation – Part II appeared first on Flavio Barros .

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More fun with %.% and %>%

March 27, 2014
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More fun with %.% and %>%

The %.% operator in dplyr allows one to put functions together without lots of nested parentheses. The flanking percent signs are R’s way of denoting infix operators; you might have used %in% which corresponds to the match function or %*% which is matrix multiplication. The %.% operator is also called chain, and what it does

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Blurry Fractals

March 27, 2014
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Blurry Fractals

Beauty is the first test; there is no permanent place in the world for ugly mathematics (G. H. Hardy) Newton basin fractals are the result of iterating Newton’s method to find roots of a polynomial over the complex plane. It maybe sound a bit complicated but is actually quite simple to understand. Those who would

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Visualizing principal components with R and Sochi Olympic Athletes

March 27, 2014
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Visualizing principal components with R and Sochi Olympic Athletes

Principal Components Analysis (PCA) is used as a dimensionality reduction method. Here we simply explain PCA step-by-step using data about Sochi Olympic Curlers. It is hard to visualize a high dimensional space. When I took linear algebra, the book and teachers spoke about it as if were easy to visualize a hyperspace, but...

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Alluvial diagrams

March 27, 2014
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Alluvial diagrams

Parallel coordinates plot is one of the tools for visualizing multivariate data. Every observation in a dataset is represented with a polyline that crosses a set of parallel axes corresponding to variables in the dataset. You can create such plots in R using a function parcoord in package MASS. For example, we can create such

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New Shiny website launched; Shiny 0.9 released

March 27, 2014
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New Shiny website launched; Shiny 0.9 released

We’re excited to introduce to you our new website for Shiny: shiny.rstudio.com! We’ve included articles on many Shiny-related topics, dozens of example applications, and an all-new tutorial for getting started. Whether you’re a beginner or expert at Shiny, we hope that having these resources available in one place will help you find the information you need.

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R User Group Activity for Q1 2014

March 27, 2014
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R User Group Activity for Q1 2014

by Joseph Rickert Worldwide R user group activity for the first Quarter of 2014 appears to be way up compared to previous years as the following plot shows. The plot was built by counting the meetings on Revolution Analytics R Community Calendar. R users continue to value the live, in person events and face-to-face meetings with their peers. Moreover,...

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