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

## Description

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

## Usage

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

## Arguments

 `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.

## Value

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

## Author(s)

Fred Viole, OVVO Financial Systems

## References

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

## Examples

 ```1 2 3 4 5 6 7 8``` ```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) ```

NNS documentation built on Feb. 17, 2018, 1:03 a.m.