by Daniel Hanson, with contributions by Steve Su (author of the GLDEX package). Part 1 of a series. Introduction As most readers are well aware, market return data tends to have heavier tails than that which can be captured by a normal distribution; furthermore, skewness will not be captured either. For ...

Last week Arthur Charpentier sketched out a Markov spatial process to generate hurricane trajectories. Here, I would like to take another look at the data Arthur used, but focus on its time component. According to the Insurance Information Institute, a normal season, based on averages from 1980 to 2010, has 12 named storms, ...

Imagine you're building a recommendation algorithm for your new online site. How do you measure its quality, to make sure that it's sending users relevant and personalized content? Click-through rate may be your initial hope…but after a bit of thought, it's not clear that it's the best metric after ...