Computes a (possibly weighted) dependence measure between `x`

and `y`

if
these are vectors. If `x`

and `y`

are matrices then the measure between the
columns of `x`

and the columns of `y`

are computed.

`wdm(x, y = NULL, method = "pearson", weights = NULL, remove_missing = TRUE)`

- x
a numeric vector, matrix or data frame.

- y
`NULL`

(default) or a vector, matrix or data frame with compatible dimensions to x. The default is equivalent to `y = x`` (but more efficient).- method
the dependence measure; see

*Details*for possible values.- weights
an optional vector of weights for the observations.

- remove_missing
if

`TRUE`

, all (pairswise) incomplete observations are removed; if`FALSE`

, the function throws an error if there are incomplete observations.

Available methods:

`"pearson"`

: Pearson correlation`"spearman"`

: Spearman's \(\rho\)`"kendall"`

: Kendall's \(\tau\)`"blomqvist"`

: Blomqvist's \(\beta\)`"hoeffding"`

: Hoeffding's \(D\) Partial matching of method names is enabled.

Spearman's \(\rho\) and Kendall's \(\tau\) are corrected for ties if there are any.

```
## dependence between two vectors
x <- rnorm(100)
y <- rpois(100, 1) # all but Hoeffding's D can handle ties
w <- runif(100)
wdm(x, y, method = "kendall") # unweighted
#> [1] 0.02331856
wdm(x, y, method = "kendall", weights = w) # weighted
#> [1] -0.04052879
## dependence in a matrix
x <- matrix(rnorm(100 * 3), 100, 3)
wdm(x, method = "spearman") # unweighted
#> [,1] [,2] [,3]
#> [1,] 1.000000000 0.008676868 -0.04549655
#> [2,] 0.008676868 1.000000000 -0.03840384
#> [3,] -0.045496550 -0.038403840 1.00000000
wdm(x, method = "spearman", weights = w) # weighted
#> [,1] [,2] [,3]
#> [1,] 1.00000000 0.02177004 0.02048581
#> [2,] 0.02177004 1.00000000 -0.01489218
#> [3,] 0.02048581 -0.01489218 1.00000000
## dependence between columns of two matrices
y <- matrix(rnorm(100 * 2), 100, 2)
wdm(x, y, method = "hoeffding") # unweighted
#> [,1] [,2]
#> [1,] 0.002378469 0.0025429314
#> [2,] -0.001035590 0.0005252796
#> [3,] 0.005232169 -0.0035272380
wdm(x, y, method = "hoeffding", weights = w) # weighted
#> [,1] [,2]
#> [1,] 0.007900614 -0.0001424806
#> [2,] -0.006867154 -0.0039366282
#> [3,] 0.007082112 -0.0032729170
```