View source: R/dependencemeasures.R
dcov | R Documentation |
Compute the distance covariance measure of Szekely, Rizzo, and Bakirov (2007) between two samples. Warning: Only valid to compute the distance covariance for two random variables X and Y. This means that X and Y cannot be random Vectors. If this is the case, consider the package energy.
dcov(x, y, Cpp = TRUE)
x |
data of first sample |
y |
data of second sample |
Cpp |
logical. If TRUE (the default), computations are performed using a C version of the code. |
See energy.
returns the sample distance covariance.
Martin Bilodeau (bilodeau@dms.umontreal.ca) and Pierre Lafaye de Micheaux (lafaye@unsw.edu.au)
Szekely, G.J., Rizzo, M.L., and Bakirov, N.K. (2007),
Measuring and Testing Dependence by Correlation of Distances,
Annals of Statistics, Vol. 35 No. 6, pp. 2769-2794.
\Sexpr[results=rd]{tools:::Rd_expr_doi("https://dx.doi.org/10.1214/009053607000000505")}
covrob
, corrob
data(stackloss)
dcov(stackloss$Air.Flow,stackloss$Water.Temp)
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