# tau: Kendall tau Rank Correlation Coefficients In ircor: Correlation Coefficients for Information Retrieval

## Description

`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.

## Usage

 ```1 2 3 4 5``` ```tau(x, y) tau_a(x, y) tau_b(x, y) ```

## Arguments

 `x` a numeric vector. In `tau_a` this is the vector of true scores. `y` a numeric vector of the same length as `x`. In `tau_a` this is the vector of estimated scores.

## Value

The correlation coefficient.

## References

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

`tauAP` for AP correlation coefficients.

## Examples

 ``` 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) ```

### Example output

``` 0.2
 0.2
 0.2
 0.2222222
 0.2247333
 0.25
```

ircor documentation built on May 2, 2019, 2:10 a.m.