I am looking for hints on how to estimate ratings for competitors in an ongoing pairwise competition using R... my particular area of interest being the game of Go, but the idea of identifying ratings (on a continuous scale) rather than relative rankings seems easily generalized to other competitions so I thought someone might be studying something related already.
I presume the rating of a competitor would be best modeled as a random variate on the rating scale, and an encounter between two competitors would be represented by a binary result. Logistic regression seems promising, but I am at a loss how to represent the model since the pairings are arbitrary and not necessarily repeated often. I have read about some approaches to estimating ratings for Go, but they seem to involve optimization using assumed distributions rather than model fitting which characterizes analysis in R. Does any of this sound familiar? Suggestions for reading, anyone? -- --------------------------------------------------------------------------- Jeff Newmiller The ..... ..... Go Live... DCN:<[EMAIL PROTECTED]> Basics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/Batteries O.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.