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

 NNS.dep R Documentation

## NNS Dependence

### Description

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

### Usage

```NNS.dep(x, y = NULL, asym = FALSE, p.value = FALSE, print.map = FALSE)
```

### Arguments

 `x` a numeric vector, matrix or data frame. `y` `NULL` (default) or a numeric vector with compatible dimensions to `x`. `asym` logical; `FALSE` (default) Allows for asymmetrical dependencies. `p.value` logical; `FALSE` (default) Generates 100 independent random permutations to test results against and plots 95 percent confidence intervals along with all results. `print.map` logical; `FALSE` (default) Plots quadrant means, or p-value replicates.

### Value

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

### Note

`NNS.cor` has been deprecated `(NNS >= 0.5.4)` and can be called via `NNS.dep`.

### Author(s)

Fred Viole, OVVO Financial Systems

### References

Viole, F. and Nawrocki, D. (2013) "Nonlinear Nonparametric Statistics: Using Partial Moments" https://www.amazon.com/dp/1490523995/ref=cm_sw_su_dp

### Examples

```## Not run:
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)

## End(Not run)
```

NNS documentation built on Jan. 8, 2023, 1:08 a.m.