It caclulates the p values that measure the correlation of pariwise rankings.
A n by m data frame, with each column representing a ranking list, which ranks the items from the most preferred to the least preferred. For missing items, use 0 to denote them.
a symmetric matrix of p values, with the (i,j)-th element denoting the p value of the i,j-th rankings.
Note that the input rankings should have at least 8 rankings. When constructing the samples of rescaled V distance for a given rank position, the number of samples should at least be 28 and the number of rankings that have items up to this position should account for at least 2/3 of the total number of rankings, otherwise the p value calculation stops at this position.
Han Li, Minxuan Xu, Jun S. Liu and Xiaodan Fan
An extended Mallows model for ranked data aggregation
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data(simu3) pvalue=corrRankings(rankings = simu3) #threshold the p values threshold=0.05 pvalue.trunc=ifelse(pvalue<=0.05, pvalue, 1) #plot the p values x=y=1:ncol(pvalue) par(mfrow=c(1,2)) image(x, y, pvalue, xlab = NA, ylab = NA, sub = "rank coefficient") image(x, y, pvalue.trunc, xlab = NA, ylab = NA, sub = "rank coefficient < 0.05")
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