After 36 years the FIFA World Cup returns to South America with the 2014 event being hosted in Brazil (after 1978 in Argentina). And as in all previous South American FIFA World Cups, a South American team is expected to take the victory: Using a bookmaker consensus rating - obtained by...

Different methods for assessing the abilities of participants in a sports tournament, and their corresponding winning probabilities for the tournament, are embedded in a common framework and their predictive performances compared. First, ratings of abilities (such as the Elo rating) are...

Four years after the last European football championship (EURO) in Austria and Switzerland, the two finalists of the EURO 2008 - Spain and Germany - are again the clear favorites for the EURO 2012 in Poland and the Ukraine. Using a bookmaker consensus rating - obtained by aggregating winning...

The paper presents an approach to the analysis of data that contains (multiple) structural changes in a linear regression setup. We implement various strategies which have been suggested in the literature for testing against structural changes as well as a dynamic programming algorithm for the...

The classical approach to testing for structural change employs retrospective tests using a historical data set of a given length. Here we consider a wide array of fluctuation-type tests in a monitoring situation – given a history period for which a regression relationship is known to be...

This paper introduces ideas and methods for testing for structural change in linear regression models and presents how these have been realized in an R package called strucchange. It features tests from the generalized uctuation test framework as well as from the F test (Chow test) framework....

Statistical graphics are often augmented by the use of color coding information contained in some variable. When this involves the shading of areas (and not only points or lines)--e.g., as in bar plots, pie charts, mosaic displays or heatmaps--it is important that the colors are perceptually...

kernlab is an extensible package for kernel-based machine learning methods in R. It takes advantage of R's new S4 ob ject model and provides a framework for creating and using kernel-based algorithms. The package contains dot product primitives (kernels), implementations of support vector...