Monthly Archives: January 2013

Item Response Modeling of Customer Satisfaction: The Graded Response Model

January 8, 2013
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Item Response Modeling of Customer Satisfaction:  The Graded Response Model

After several previous posts introducing item response theory (IRT), we are finally ready for the analysis of a customer satisfaction data set using a rating scale.  IRT can be multidimensional, and R is fortunate to have its own package, mirt, with excellent documentation (R.Philip Chalmers).  But, the presence of a strong first principal...

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Annoucing the Rcpp Gallery

January 8, 2013
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Earlier this morning, JJ announced what we had been working on for the last few weeks: the Rcpp Gallery. Now, as our luck will have it, the Rcpp-devel list received his message but did not transmit it for an apparent mail system outage at WU Vienna:...

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2013-1 TimingManager: Animation Sequences in JavaScript

January 8, 2013
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The TimingManager library is a tool written in JavaScript used to apply animations in a web browser. It is not concerned with creation or modification of animation timing information, and delegates those tasks to R via the animaker package. Primarily … Continue reading →

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Data Mining with R course taught by Luis Torgo

January 8, 2013
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From the 25th of march onwards, Dr. Luis Torgo will teach a Data Mining with R course together with the DIKW Academy in Nieuwegein, The Netherlands. Dr. Torgo is an Associate Professor at the department of Computer Science at the… See more ›

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R 101

January 8, 2013
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(This article was first published on Just Another R Blog, and kindly contributed to R-bloggers) To leave a comment for the author, please follow the link and comment on their blog: Just Another R Blog. R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps,...

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Integrating Rmathlib and kdb+

January 8, 2013
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The R engine is usable in a variety of ways – one of the lesser-known features is that it provides a standalone math library that can be linked to from an external application. This library provides some nice functionality such … Continue reading →

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Decomposition: The Statistics Software Signal

January 8, 2013
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From: Decomposition: The Statistics Software Signal http://seanjtaylor.com/post/39573264781/the-statistics-software-signal"When you don't have to code your own estimators, you probably won't understand what you're doing. I'm not saying that you defini...

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Data science = failure of imagination

January 8, 2013
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From: http://www.r-bloggers.com/data-driven-science-is-a-failure-of-imagination/I think I like this distinction between Bayesian and Frequentist statistics: "we are nearly always ultimately curious about the Bayesian probability of the hypothesis ...

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Interactive MDS visualisation using D3

January 8, 2013
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Interactive MDS visualisation using D3

Here’s a sneak peak into upcoming visualisation work. I’ve been working a bit on MDS (Multi-dimensional scaling), a classical technique for visualising distance data. Classical MDS is useful, but interactive MDS is *much* more useful. Using D3, a Javascript visualisation framework, it’s relatively easy to make interactive MDS plots. This example shows how basic interaction

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R-package: Wilcox’ Robust Statistics updated (WRS v0.20)

January 8, 2013
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Rand Wilcox constantly updates the functions accompanying his books on robust statistics. Recently, they have been updated to version 20. The functions are available in the WRS package for R – for installation simply type install.packages("WRS", repos="http://R-Forge.R-project.org") In version 0.20, a number of functions dealing with ANCOVA have been added and some others improved. Unfortunately,

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