If you are interested in my Super Rugby and NRL predictions they can be found on the Statistics Department blog Stats Chat.

The method used for these predictions is very simple. To predict the outcome of a game I estimate the margin as the home team rating minus the away team rating, plus the home ground advantage value. If the margin is positive, the home team is predicted as the winner. If it is negative, the away team is predicted as the winner. Ratings for the teams are adjusted after the game using the error correction form of exponential smoothing. Obviously there is some initial estimation of team ratings, and some choice of the optimum parameter values for the exponential smoothing constant and the home ground advantage. Once these tasks are complete, the prediction routine can be run automatically.

It's not rocket science, just statistics.

This year I am teaching STATS 779 Professional Skills for Statisticians jointly with James Curran, STATS 320 Applied Stochastic Modelling, and part of STATS 370 Financial Mathematics. STATS 779 ranges broadly over a range of software which is of use to professional and research statisticians. STATS 782 is a predecessor of STATS 799. For both courses I have collected a range of documentation which I have found useful both in my own work and in teaching. Go to the pages STATS 779 or STATS 782 to access this material.

STATS 779 | Web page for STATS 779, Professional Skills for Statisticians |

STATS 782 | Home page for STATS 782, Computing for Statisticians |

My most recent package is hwriterPlus which is a package for Reproducible Research or automated report writing. It extends the package hwriter which is on CRAN. Here is the description for hwriterPlus.

"This package extends the package hwriter providing facilities such as the inclusion of output from R, the results of an R session, the display of mathematical expressions using LaTeX notation and the incorporation of SVG graphical objects."

hwriterPlus contains an extensive example showing how it may be
used. The file used is called `BrowserExample.R`

which
produces an html file called `BrowserExample.html`

. These
files may be found in the directory `examples`

in the
`inst`

directory of the package.

There is also a vignette describing the package, named
`hwriterPlus.pdf`

which is in the directory
`doc`

in the `inst`

directory of the
package.

I have developed a number of packages for distributions which are available on CRAN. Currently these are DistributionUtils, GeneralizedHyperbolic, SkewHyperbolic, and VarianceGamma.

My R package HyperbolicDist is still available on CRAN, but deprecated since it has been replaced by DistributionUtils and GeneralizedHyperbolic.

Development versions of my packages are all available on R-Forge as part of the Rmetrics project. This link Rmetrics packages on R-Forge will take you to those packages.

In addition to the packages mentioned above there is a package for the normal Laplace distribution on R-Forge which is not yet on CRAN.

There are some other functions which I have not yet included in my packages. Most of them are alternative methods of simulation of generalized hyperbolic observations.

These functions may be downloaded and used provided the the source is acknowledged.

hyperbReg.R | Fit a regression with hyperbolic errors |

rgig1.R | Generate observations from the generalized inverse Gaussian distribution with lambda = 1 |

rgigJD.R | Generate observations from the generalized inverse Gaussian distribution using Dagpunar's algorithm |

rgigJD1.R | Generate observations from the generalized inverse Gaussian distribution using Dagpunar's algorithm, with lambda = 1 |

rgigTDR1.R | Generate observations from the generalized inverse Gaussian distribution using transformed density rejection algorithm, with lambda = 1 |

rhypJD.R | Generate observations from the hyperbolic distribution using the mixing property of the generalised inverse Gaussian distribution and Dagpunar's algorithm for the generalised inverse Gaussian |

rhypRoU.R | Generate observations from the hyperbolic distribution using the ratio of uniforms method |

rhypSS.R | Generate observations from the hyperbolic distribution using the slice sampler |

rhypTDR.R | Generate observations from the hyperbolic distribution using transformed density rejection |

rhypTDRsq.R | Generate observations from the hyperbolic distribution using transformed density rejection with a squeeze function |

I use BEAMER for the production of pdf slides using LaTeX. Here are some example slides and the LaTeX files used to produce them. These were used in a presentation to staff and students in the Department of Statistics on June 10, 2008.

Beamer.pdf | Slides used in the presentation and the LaTeX file Beamer.tex used to prepare them. Don't expect the movie to work, in fact clicking on "Click for Movie" crashes my browser. |

Examples.pdf | A pdf prepared using BEAMER and showing the use of overlays, with the default BEAMER theme. The file used to produce the examples, Examples.tex has commented out themes of various sorts which can be used to experiment to find a theme you like. I never got the ComicSans font option to work. Maybe you will have better luck. |

Themes.pdf | A pdf showing the effect of various themes, produced by abstracting the test slide from the Examples.pdf using different themes. |