NNS.dep: NNS Dependence
In NNS: Nonlinear Nonparametric Statistics

Description Usage Arguments Value Author(s) References Examples

Returns the dependence and nonlinear correlation between two variables based on higher order partial moment matrices measured by frequency or area.

1	NNS.dep(x, y = NULL, order = NULL, degree = NULL, print.map = FALSE)

`x`	a numeric vector, matrix or data frame.
`y`	`NULL` (default) or a numeric vector with compatible dimsensions to `x`.
`order`	integer; Controls the level of quadrant partitioning. Defaults to `(order = NULL)`. Errors can generally be rectified by setting `(order = 1)`. Will not partition further if less than 4 observations exist in a quadrant.
`degree`	integer; Defaults to NULL to allow number of observations to be `"degree"` determinant.
`print.map`	logical; `FALSE` (default) Plots quadrant means.

Returns the bi-variate "Correlation" and "Dependence" or correlation / dependence matrix for matrix input.

Fred Viole, OVVO Financial Systems

Viole, F. and Nawrocki, D. (2013) "Nonlinear Nonparametric Statistics: Using Partial Moments" http://amzn.com/1490523995

set.seed(123)
x <- rnorm(100) ; y <- rnorm(100)
NNS.dep(x, y)

## Correlation / Dependence Matrix
x <- rnorm(100) ; y <- rnorm(100) ; z <- rnorm(100)
B <- cbind(x, y, z)
NNS.dep(B)