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...

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...

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

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...

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...

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...

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

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