# 726 search results for "parallel"

## the Art of R Programming [guest post]

January 30, 2012
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(This post is the preliminary version of a book review by Alessandra Iacobucci, to appear in CHANCE. Enjoy !) As Rob J. Hyndman enthusiastically declares in his blog, “this is a gem of a book”. I would go even further and argue that The Art of R programming is a

## CBC Reviews: Revolution R (in which this doesn’t go well)

January 24, 2012
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Update!: The latest version of Revolution R, which added support for RHEL 6, appears to work (it appears to at least install, run, and perform basic tasks). See this post for more details. I’ve come to enjoy using R. I had dabbled with it in the past, but found it painfully opaque, and the Effort:Reward

## Interactive Graphics with the iplots Package (from “R in Action”)

January 24, 2012
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(This article was first published on R-statistics blog » R, and kindly contributed to R-bloggers) The followings introductory post is intended for new users of R.  It deals with interactive visualization using R through the iplots package. This is a guest article by Dr. Robert I. Kabacoff, the founder of (one of) the first online R tutorials websites: Quick-R. Kabacoff has...

## R in the cloud

January 19, 2012
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Psychometrics, Qu’est-ce que c’est?Say psychometrics to people and they think IQ tests. Fair enough.I think eRm:1 2 3 4 5 6 7# Rasch model with beta.1 restricted to 0 data(raschdat1) res <- RM(raschdat1, sum0 = FALSE) print(res) summary(res) res\$W The joy of fitting your first Rasch model in R is unparallelled. Go on try, it. Hmmm, a list of numbers. No idea what they mean?ok. so you take an IQ...

## Improve Predictive Performance in R with Bagging

January 18, 2012
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Bagging, aka bootstrap aggregation, is a relatively simple way to increase the power of a predictive statistical model by taking multiple random samples(with replacement) from your training data set, and using each of these samples to construct a separate model and separate predictions for your test set. These predictions are then averaged to create a, hopefully more accurate,...

## Improve Predictive Performance in R with Bagging

January 18, 2012
By

Bagging, aka bootstrap aggregation, is a relatively simple way to increase the power of a predictive statistical model by taking multiple random samples(with replacement) from your training data set, and using each of these samples to construct a separate model and separate predictions for your test set. These predictions are then averaged to create a, hopefully more accurate, final...

## Sorting in R as Inefficiently as Possible

January 12, 2012
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$Sorting in R as Inefficiently as Possible$

My last post of substance was all about improving your performance using R to answer programming questions that might be asked during a job interview.  So let's say you nailed the interview and got the job, but you desperately want to be fired for grand incompetence.  Never fear, your pal at librestats once again has your back. The sleep...

## Honing Your R Skills for Job Interviews

January 9, 2012
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My time as a grad student will soon draw to a close. With this comes the terrifying realisation that I'm going to start applying for jobs and, hopefully, interviewing soon, forever leaving my comfortable security blanket of academia. With that horrible thought in mind, I've been doing some poking around to see what various kinds of technical interviews are...

## 1500th, 3000th, &tc

January 7, 2012
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As the ‘Og reached its 1500th post and 3000th comment at exactly the same time, a wee and only mildly interesting Sunday morning foray in what was posted so far and attracted the most attention (using the statistics provided by wordpress). The most visited posts: Title Views Home page 203,727 In{s}a(ne)!! 7,422 “simply start over