wdm | R Documentation |
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 |
|
method |
the dependence measure; see Details for possible values. |
weights |
an optional vector of weights for the observations. |
remove_missing |
if |
Available methods:
"pearson"
: Pearson correlation
"spearman"
: Spearman's ρ
"kendall"
: Kendall's τ
"blomqvist"
: Blomqvist's β
"hoeffding"
: Hoeffding's D
Partial matching of method names is enabled.
Spearman's ρ and Kendall's τ 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 wdm(x, y, method = "kendall", weights = w) # weighted ## dependence in a matrix x <- matrix(rnorm(100 * 3), 100, 3) wdm(x, method = "spearman") # unweighted wdm(x, method = "spearman", weights = w) # weighted ## dependence between columns of two matrices y <- matrix(rnorm(100 * 2), 100, 2) wdm(x, y, method = "hoeffding") # unweighted wdm(x, y, method = "hoeffding", weights = w) # weighted
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.