Statistical Calculations & Numerical Accuracy
This post is for those readers who’re getting involved with economic statistics for the first time. Basically, it serves as a warning that sometimes the formulae that you learn about have to be treated with care when it comes to the actual numerical implementation. Sometimes (often) there’s more than one way to express the formula for some statistic. While thee formulae may be mathematically identical, they can yield different numerical results when you go to apply them. Yes, this sounds counter-intuitive, but it’s true. And it’s all to do with the numerical precision that your calculator (computer) is capable of.

Overfitting or generalized? Comparison of ML classifiers – a series of articles
In my own blog I wrote a series of articles about how major machine learning classifiers work, with some visualization of their decision boundaries on various datasets.

A Better ZigZag
There are a lot of ‘winning’ strategies for bull markets floating around. ‘Buy the pullbacks’ is certainly one of them. Does this sound simple enough to implement to you? While I am no Sheldon Cooper (although I have a favorite couch seat), I still like to live in a somewhat well defined world, a world in which, there is much more information attached to a tip like ‘Buy the pullbacks’.

Macros in R
In programming, sometimes it’s useful to write a macro rather than a function. (Don’t worry if you’ve never heard the term before.) In this post, I’ll give an example of use of macros in R. using the gtools package on CRAN.