A bug-fix release RQuantLib 0.3.8 is now on CRAN and in Debian. RQuantLib combines (some of) the quantitative analytics of QuantLib with the R statistical computing environment and language.Thanks to Helmut Heiming who noticed a side-effec t f...

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A bug-fix release RQuantLib 0.3.8 is now on CRAN and in Debian. RQuantLib combines (some of) the quantitative analytics of QuantLib with the R statistical computing environment and language.Thanks to Helmut Heiming who noticed a side-effec t f...

Sometimes it is convenient to use “call by reference evaluation” inside an R function. For example, if you want to have multiple return value for your function, then either you return a list of return value and split them afterward or you can return the value via the argument. For some reasons(I would like to

When I received this book, Handbook of fitting statistical distributions with R, by Z. Karian and E.J. Dudewicz, from/for the Short Book Reviews section of the International Statistical Review, I was obviously impressed by its size (around 1700 pages and 3 kilos…). From briefly glancing at the table of contents, and the list of standard

I was recently asked how to implement time series cross-validation in R. Time series people would normally call this “forecast evaluation with a rolling origin” or something similar, but it is the natural and obvious analogue to leave-one-out cross-validation for cross-sectional data, so I prefer to call it “time series cross-validation”. Here is some example

“In the end, it really is just a matter of choosing the relevant parts of mathematics and ignoring the rest. Of course, the hard part is deciding what is irrelevant.” Somehow, I had missed the first edition of this book and thus I started reading it this afternoon with a newcomer’s eyes (obviously, I will

A simple yet efficient way to work with R consists in writing R code with your favorite text editor and sending it to the R console. This allows to build efficient R code in an incremental fashion. A good editor might even provide syntax highlighting, parenthesis matching, and a way to send a selected portion of code to R

One of the recurring frustrations in data analytics is that your data is never in the right shape. Worst case: you are not aware of this and every step you attempt is more expensive, less reliable and less informative than you would want. Best case: you notice this and have the tools to reshape yourRelated posts:

NppToR 2.6 is coming with improved flexibility and speed. Testers needed before setting as default.