First steps in using C++11 with Rcpp

January 9, 2013
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The recent release of the C++11 standard has brought a lot of attention to the new language features. Rcpp, as a CRAN package, follows CRAN policy in not (yet!!) supporting the standard for its purported non-portable status. Even as of the current g++ ...

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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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Remembering server installation details

January 8, 2013
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Remembering server installation details

I’ve been moving part of my work to university servers, where I’m just one more peasant user with little privileges. In exchange, I can access the jobs from anywhere and I can access multiple processors if needed. Given that I have a sieve-like memory, where configuration details quickly disappear through many small holes, I’m documenting

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Speeding up R computations Pt III: parallelization

January 8, 2013
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In two previous posts, I have written about how you can speed up your R computations either by using strange notation and non-standard functions or by compiling your code. Last year my department bought a 64-core computational server, which allowed me ...

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Open Science Challenge

January 8, 2013
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Open Science Challenge

Open Science Science is becoming more open in many areas: publishing, data sharing, lab notebooks, and software. There are many benefits to open science. For example, sharing research data alongside your publications leads to increased citation ra...

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Handling Strings with Rcpp

January 8, 2013
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This is a quick example of how you might use Rcpp to send and receive R ‘strings’ to and from R. We’ll demonstrate this with a few operations. Sort a String with R Note that we can do this in R in a fairly fast way: my_strings <-...

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Using Rcout for output synchronised with R

January 8, 2013
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The Writing R Extensions manual, which provides the gold standard of documentation as far as extending R goes, suggests to use Rprintf and REprintf for output (from C/C++ code) as these are matched to the usual output and error streams maintained by R ...

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Open Science Challenge

January 8, 2013
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Open Science Challenge

Open Science Science is becoming more open in many areas: publishing, data sharing, lab notebooks, and software. There are many benefits to open science. For example, sharing research data alongside your publications leads to increased citation ra...

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Reserving based on log-incremental payments in R, part I

January 8, 2013
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A recent post on the PirateGrunt blog on claims reserving inspired me to look into the paper Regression models based on log-incremental payments by Stavros Christofides , published as part of the Claims Reserving Manual (Version 2) of the Institute of Actuaries.The paper is available together with a spread sheet model, illustrating the calculations. It...

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Improving Twitter Search with Real-Time Human Computation

January 7, 2013
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(This is a post from the Twitter Engineering Blog that I wrote with Alpa Jain.) One of the magical things about Twitter is that it opens a window to the world in real-time. An event happens, and just seconds later, it’s shared for people across the planet to see. Consider, for example, what happened when...

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The myth of the missing Data Scientist

January 7, 2013
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The myth of the missing Data Scientist

Much has been said about the dire shortage of Data Scientists looming on the horizon. With the spectre of Big …Continue reading »

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Does anything NOT beat the GARCH(1,1)?

January 7, 2013
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Does anything NOT beat the GARCH(1,1)?

In their paper on GARCH model comparison, Hansen and Lunde (2005) present evidence that among 330 different models, and using daily data on the DM/$ rate and IBM stock returns, no model does significantly better at predicting volatility (based on a realized measure) than the GARCH(1,1) model, for an out of sample period of about

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Does anything NOT beat the GARCH(1,1)?

January 7, 2013
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Does anything NOT beat the GARCH(1,1)?

In their paper on GARCH model comparison, Hansen and Lunde (2005) present evidence that among 330 different models, and using daily data on the DM/$ rate and IBM stock returns, no model does significantly better at predicting volatility (based on a realized measure) than the GARCH(1,1) model, for an out of sample period of about

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Creating a Covariance Matrix from Scratch

January 7, 2013
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I have been conducting several simulations that use a covariance matrix.  I needed to expand the code that I found in the psych package to have more than 2 latent variables (the code probably allows it but I didn’t figure it out).  I ran across Joreskog’s 1971 paper and realized that I could use the confirmatory factor analysis...

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Creating a Covariance Matrix from Scratch

January 7, 2013
By

I have been conducting several simulations that use a covariance matrix.  I needed to expand the code that I found in the psych package to have more than 2 latent variables (the code probably allows it but I didn’t figure it out).  I ran across Joreskog’s 1971 paper and realized that I could use the confirmatory factor analysis...

Read more »

Speed trick: unlist(…, use.names=FALSE) is heaps faster!

January 7, 2013
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Sometimes a minor change to your R code can make a big difference in processing time. Here is an example showing that if you're don't care about the names attribute when unlist():ing a list, specifying argument use.names=FALSE can speed up the process...

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Setting up emacs org-mode babel for R on Ubuntu

January 7, 2013
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Setting up emacs org-mode babel for R on Ubuntu

I installed org-mode seperately, since I had troubles with its default setting (similar to the problems described here). sudo apt-get install org-mode Next I download and installed ESS cd ~/.emacs.d/ wget http://ess.r-project.org/downloads/ess/ess-12.09-1.zip unzip ess-12.09-1.zip rm ess-12.09-1.zip Finally I had to … Continue reading →

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R/Finance 2013: May 17-18 in Chicago

January 7, 2013
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This year's R/Finance conference on applied finance with R is scheduled for May 17-18 in Chicago, and promises once again to be the go-to conference for anyone using R in the finance industry. The keynote speakers have been announced, and it's a great lineup: Sanjiv Das, Professor of Finance and Chair of Finance Dept, Santa Clara University’s Leavey School...

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Breaking the rules with spatial correlation

January 7, 2013
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Breaking the rules with spatial correlation

Students in any basic statistics class are taught linear regression, which is one of the simplest forms of a statistical model. The basic idea is that a ‘response’ variable can be mathematically related to one or any number of ‘explanatory’ variables through a linear equation and a normally distributed error term. With any statistical tool,

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Don’t R alone! A guide to tools for collaboration with R

January 7, 2013
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Don’t R alone! A guide to tools for collaboration with R

This a brief guide to using R in collaborative, social ways. R is a powerful open-source programming language for data analysis, statistics, and visualization, but much of its power derives from a large, engaged community of users. This is an introduction to tools for engaging the community to improve your R code and collaborate with others. (Am I...

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