# taba: Robust Correlation In Taba: Taba Robust Correlations

## Description

Returns the Taba robust linear, Taba rank (monotonic), TabWil, or TabWil rank correlation coefficient between two numeric vectors.

## Usage

 `1` ```taba(x, y, method = c("taba", "tabarank","tabwil", "tabwilrank"), omega) ```

## Arguments

 `x` A numeric vector of length greater than 2 must be same length as y `y` A numeric vector of length greater than 2 must be same length as x `method` A character string of `"taba"`, `"tabarank"`, `"tabwil"`, or `"tabwilrank"` determining if one wants to calculate Taba linear, Taba rank (monotonic), TabWil, or TabWil rank correlation, respectively. If no method is specified, the function will output Taba Linear correlation. `omega` Numeric allowing the user to alter the tuning constant. If one is not specified, the function will default to 0.45 for Taba and Taba rank, and 0.1 for TabWil and TabWil rank. Range is between 0 and 1.

## Details

This function can be used to compare two non-empty numeric vectors of length greater than two, or two columns of a data frame or matrix composed of more than two numeric elements. Missing values in either x or y are deleted row-wise. The default method is Taba Linear correlation, with the tuning constant `omega`.

## Value

This function returns a the robust linear or monotonic association between two numeric vectors as a numeric.

## References

The paper is under review for possible publication.

`taba.test` for testing Taba linear or Taba rank (monotonic) correlations
`taba.partial` for partial and semipartial correlations
`taba.gpartial` for generalized partial correlations
`taba.matrix` for calculating correlation, p-value, and distance matricies
 ```1 2 3 4 5``` ```x = rnorm(100) y = rnorm(100) taba(x, y) taba(x, y, method = "tabarank", omega = 0.4) taba(x, y, method = "tabwil", omega = 0.22) ```