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 \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
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
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