library(StratTourn) library(shiny) library(xtable) library(knitr) setwd("D:/libraries/StratTourn") tourn = load.tournament("Tourn_Noisy_PD_20140721_202445.Rdata") # Data for each match md = tourn$dt md = add.other.var(md,c("strat","u")) md$delta.u = md$u - md$other.u # Names of all strategies strats = unique(md$strat) used.strats = strats shown.strats = strats
view(strat.rank.from.matches(md))
Note: The sigma.rank of a strategy i is given by 1 plus the number of strategies j whose payoff is larger by more than the sum of standard errors for i and j. This means strategies whose payoffs are statistically too close to each other can have the same sigma.rank.
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