With all my recent focus on reporting and visualization, you might think that I have the investments all figured out. Unfortunately, that is not the case, and I will resume more standard investment and systems posts soon. I did want to shar...
Monthly Archives: February 2012
The anatomy of a Twitter conversation, visualized with R
If you're a Twitter user like me, you're probably familiar with the way that conversations can easily by tracked by following the #hashtag that participants include in the tweets to label the topic. But what causes some topics to take off, and others to die on the vine? Does the use of retweets (copying another users tweet to your...
General Bayesian estimation using MHadaptive
If you can write the likelihood function for your model, MHadaptive will take care of the rest (ie. all that MCMC business). I wrote this R package to simplify the estimation of posterior distributions of arbitrary models. Here’s how it works: 1) Define your model (ie the likelihood * prior). In this example, lets build 
Using apply() to create a unique id
Suppose you have a data set with two identifiers. For example, maybe you're studying the relationships among firms in an industry and you have a way to link the firms to one another. Each firm has an id, but the unique unit in your data set is a pair...
An R script for estimating future inflation via the Treasury market
One factor that is critical for any financial planning is estimating what future inflation will be. For example, if you’re saving money in an instrument that gains 3% per year, and inflation is estimated to be 4% per year, well then you’re losing m...
Visualising Activity Around a Twitter Hashtag or Search Term Using R
I think one of valid criticisms around a lot of the visualisations I post here and on my various #f1datajunkie blogs is that I often don’t post any explanatory context around the visualisations. This is partly a result of the way I use my blog posts in a selfish way to document the evolution of 
The US market will absolutely positively definitely go up in 2012
The Super Bowl tells us so. The Super Bowl Indicator The championship of American football decides the direction of the US stock market for the year. If a “National” team wins, the market goes up; if an “American” team wins, the market goes down. Yesterday the Giants, a National team, beat the Patriots. The birth … Continue reading...
googleVis 0.2.14 is released
Version 0.2.14 of the googleVis package was released on CRAN today.ChangesThe help files have been checked against changes of the Google Visualisation API, typos in the vignette have been ironed out (thanks to Pat Burns for pointing them out), a new se...
Comparing correlations update
I have just published R code for calculating CIs for differences between correlations on the Serious stats book blog. This covers independent correlations (taken from chapter 6 of the book) and dependent correlations (new R code written as a suppl...
Comparing correlations: independent and dependent (overlapping or non-overlapping)
In Chapter 6 (correlation and covariance) I consider how to construct a confidence interval (CI) for the difference between two independent correlations. The standard approach uses the Fisher z transformation to deal with boundary effects (the squashing of the distribution and increasing asymmetry as r approaches -1 or 1). As zr is approximately normally distributed 
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
