As stated in CloudStat Intro, we know that CloudStat is based on R Language, an object orientated language, everything in R is an object. Each object has a class. The simplest data objects are one-dimensional arrays called vectors, consisting of any nu...
Monthly Archives: November 2011
The Joy of R: A Feline Guide
Just because it’s caturday Images by Mario Pineda-Krch (CC BY-NC-SA 3.0) This is from the “Mario’s Entangled Bank” blog ( http://pineda-krch.com ) of Mario Pineda-Krch, a theoretical biologist at the University of Alberta. Filed under: cats, computing, humour, R, Sweave
Colour wheels in R
Regular readers will know I use the R package to produce most of the charts that appear here on the blog. Being more quantitative than artistic, I find choosing colours for the charts to be one of the trickiest tasks when designing a chart, particularly as R has so many colours to choose from. In
Data Referenced Journalism and the Media – Still a Long Way to Go Yet?
Reading our local weekly press this evening (the Isle of Wight County Press), I noticed a page 5 headline declaring “Alarm over death rates at St Mary’s”, St Mary’s being the local general hospital. It seems a Department of Health report on hospital mortality rates came out earlier this week, and the Island’s hospital, it 
Unit root versus breaking trend: Perron’s criticism
I came across an ingenious simulation by Perron during my Time-series lecture which I thought was worth sharing. The idea was to put your model to a further test of breaking trend before accepting the null of unit root. Let me try and illustrate this in simple language.
A non-stationary time series is one that has its mean changing...
Generating PPC Keywords in R – Part 2
In a previous post, I discussed how to generate PPC keywords in R. In this post I will provide another example of how to perform this task. Let’s say that I am a auto insurance company that only operates in the state of Illinois. I’m planing on bidding on keywords in Bing and Google which
Rdatamarket Tutorial
The good folks at DataMarket have posted a new tutorial on using the rdatamarket package (covered here in August) to easily download public data sets into R for analysis. The tutorial describes how to install the rdatamarket package, how to extract metadata for data sets, and how to download the data themselves into R. The tutorial also illustrates a...
Confidence interval for predictions with GLMs
Consider a (simple) Poisson regression . Given a sample where , the goal is to derive a 95% confidence interval for given , where is the prediction. Hence, we want to derive a confidence interval for the prediction, not the potential observation...
Confidence interval for predictions with GLMs
Consider a (simple) Poisson regression . Given a sample where , the goal is to derive a 95% confidence interval for given , where is the prediction. Hence, we want to derive a confidence interval for the prediction, not the potential observation, i.e. the dot on the graph below > r=glm(dist~speed,data=cars,family=poisson) > P=predict(r,type="response", + newdata=data.frame(speed=seq(-1,35,by=.2))) > plot(cars,xlim=c(0,31),ylim=c(0,170)) > abline(v=30,lty=2)...
Factor to class-membership matrix
Recently on R-bloggers I found a post from chem-bla-ics blog concerning conversion of factors to integer vectors. At the end it stated a problem of conversion of factor variable to class-membership matrix. In comments several nice solutions were p...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
