People rave about Sweave and the literate programing paradigm and I am guilty as charged. I speak Sweave, I think Sweave, I dream Sweave. As a matter of fact my default mode of operation is Sweave and anything else is an … Continue reading →

The new RQuantLib release 0.3.5 is now on CRAN and in Debian. RQuantLib combines (some of) the quantitative analytics of QuantLib with the R statistical computing environment and language. Most of the changes were made two and four weeks ago: fir...

This post provides an example of using Sweave to perform an item analysis of a multiple choice test. It is designed as a tutorial for learning more about using Sweave in a mode where console input and output is displayed. Copies of all source code a...

This post provides an example of using Sweave to perform an item analysis of a multiple choice test. It is designed as a tutorial for learning more about using Sweave in a mode where console input and output is displayed. Copies of all source code a...

The Holt-Winters method is a popular and effective approach to forecasting seasonal time series. But different implementations will give different forecasts, depending on how the method is initialized and how the smoothing parameters are selected. In this post I will discuss various initialization methods. Suppose the time series is denoted by and the seasonal period

An interesting note was arXived a few days ago by Madeleine Thompson and Radford Neal. Beside the nice touch of mixing crumbs and slices, the neat idea is to have multiple-try proposals for simulating within a slice and to decrease the dimension of the simulation space at each try. This dimension diminution is achieved via

This post provides information on (a) installing Git using the Eclipse plugin Egit. (b) uploading repositories to GitHub, and (c) links to resources on Git, Git and LaTeX, and Git and R. The focus is on version control for people working on R, Sweave, ...

This post provides information on (a) installing Git using the Eclipse plugin Egit. (b) uploading repositories to GitHub, and (c) links to resources on Git, Git and LaTeX, and Git and R. The focus is on version control for people working on R, Sweave, ...

The book Random effects and latent variable model selection, edited by David Dunson in 2008 as a Springer Lecture Note. contains several chapters dealing with evidence approximation in mixed effect models. (Incidentally, I would be interested in the story behind the Lecture Note as I found no explanation in the backcover or in the preface.

As I mentioned in a recent post, I’ve just received a copy of Advanced Markov Chain Monte Carlo Methods. Chapter 1.4 in the book (very quickly) covers random variable generation. Inverse CDF Method A standard algorithm for generating random numbers is the inverse cdf method. The continuous version of the algorithm is as follows: 1.