NNS.copula {NNS} | R Documentation |
NNS Co-Partial Moments Higher Dimension Dependence
Description
Determines higher dimension dependence coefficients based on co-partial moment matrices ratios.
Usage
NNS.copula(
X,
target = NULL,
continuous = TRUE,
plot = FALSE,
independence.overlay = FALSE
)
Arguments
X |
a numeric matrix or data frame. |
target |
numeric; Typically the mean of Variable X for classical statistics equivalences, but does not have to be. (Vectorized) |
continuous |
logical; |
plot |
logical; |
independence.overlay |
logical; |
Value
Returns a multivariate dependence value [0,1].
Author(s)
Fred Viole, OVVO Financial Systems
References
Viole, F. (2016) "Beyond Correlation: Using the Elements of Variance for Conditional Means and Probabilities" https://www.ssrn.com/abstract=2745308.
Examples
## Not run:
set.seed(123)
x <- rnorm(1000) ; y <- rnorm(1000) ; z <- rnorm(1000)
A <- data.frame(x, y, z)
NNS.copula(A, target = colMeans(A), plot = TRUE, independence.overlay = TRUE)
### Target 0
NNS.copula(A, target = rep(0, ncol(A)), plot = TRUE, independence.overlay = TRUE)
## End(Not run)