Axys, R, d3.js, and HTML5 all offer incredibly powerful tools for investment management and reporting, but they are not set up to synergistically interact to fill each other’s gaps and leverage each other’s strengths. In my ideal scenario, Ax...

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Approximate Bayesian Computing and similar techniques, which are based on calculating approximate likelihood values based on samples from a stochastic simulation model, have attracted a lot of attention in the last years, owing to their promise to provide a general statistical technique for stochastic processes of any complexity, without the limitations that apply to “traditional”…

Many public agencies release data in a fixed-format ASCII (FWF) format. But with the data all packed together without separators, you need a "data dictionary" defining the column widths (and metadata about the variables) to make sense of them. Unfortunately, many agencies make such information available only as a SAS script, with the column information embedded in a PROC...

Geography is often about statistics as it is the basis for fast exchange of information: providing a mean and standard deviation to the audience is often much easier then showing raw data: Learning a script language for this purpose can be a hard-ass work. But I think it is more often a need of practice.

The ggplot2 package provides an excellent platform for data visualization. One (minor) drawback of this package is that combining ggplot images into one plot, like the par() function does for regular plots, is not a straightforward procedure. Fortunately, R user Stephen Turner has kindly provided a function called “arrange” that does exactly this. The function,