Description Usage Arguments Value References See Also Examples

`tau`

is the rank correlation coefficient by Kendall, where neither vector can contain tied
items. `tau_a`

and `tau_b`

are the versions developed to cope with ties under the
scenarios of accuracy and agreement, respectively. See the references for details.

1 2 3 4 5 |

`x` |
a numeric vector. In |

`y` |
a numeric vector of the same length as |

The correlation coefficient.

M.G. Kendall (1970). Rank Correlation Methods. Charles Griffin & Company Limited.

`tauAP`

for AP correlation coefficients.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
# No ties
x <- c(0.67, 0.45, 0.29, 0.12, 0.57, 0.24, 0.94, 0.75, 0.08, 0.54)
y <- c(0.48, 0.68, 0.32, 0.09, 0.06, 0.61, 0.87, 0.22, 0.44, 0.84)
tau(x, y)
tau_a(x,y) # same as tau
tau_b(x,y) # same as tau
# Ties in y
y <- round(y, 1)
tau_a(x, y)
tau_b(x, y)
# Ties in x too
x <- round(x, 1)
tau_b(x, y)
``` |

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