Description Usage Arguments Value Note Author(s) References Examples

It caclulates the p values that measure the correlation of pariwise rankings.

1 | ```
corrRankings(rankings)
``` |

`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. |

`pair.pvalue` |
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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
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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