Abstract. Choosing between different tournament designs based on their accuracy in ranking teams is an important topic in football since many domestic championships underwent changes in the recent years. In particular, the transformations of Ekstraklasa -- the top-tier football competition in Poland -- is a topic receiving much attention from the organizing body of the competition, participating football clubs as well as supporters. In this presentation we will discuss the problem of measuring the accuracy of different league formats in ranking teams. We will present various models for rating teams that will be next used to simulate a number of tournaments to evaluate their efficacy, for example, by measuring the probability of the best team win. Finally, we will discuss several other aspects of league formats including the influence of the number of points allocated for a win on the final league standings.
Abstract. Since the classic work of de Sola Price the rich-gets-richer rule is well known as the most important mechanism governing the citation network dynamics. (Un-)Fortunatelly it is not sufficient to explain every aspect of bibliometric data. Using the proposed agent-based model for the bibliometric networks we will shed some light on the problem and try to answer the important question stated in the title. Joint work with A. Cena, M. Gagolewski and B. Żogała-Siudem.
Ris on CRAN. The package is one of the most downloaded R extensions and provides a rich set of string processing procedures.
* [WINDOWS SPECIFIC] #270: Strings marked with `latin1` encoding are now converted internally to UTF-8 using the WINDOWS-1252 codec. This fixes problems with - among others - displaying the Euro sign. * [NEW FEATURE] #263: Add support for custom rule-based break iteration, see `?stri_opts_brkiter`. * [NEW FEATURE] #267: `omit_na=TRUE` in `stri_sub<-` now ignores missing values in any of the arguments provided. * [BUGFIX] fixed unPROTECTed variable names and stack imbalances as reported by rchk
Abstract. As cities increase in size, governments and councils face the problem of designing infrastructure and approaches to traffic management that alleviate congestion. The problem of objectively measuring congestion involves taking into account not only the volume of traffic moving throughout a network, but also the inequality or spread of this traffic over major and minor intersections. For modelling such data, we investigate the use of weighted congestion indices based on various aggregation and spread functions. We formulate the weight learning problem for comparison data and use real traffic data obtained from a medium-sized Australian city to evaluate their usefulness.