# circlin.cor: Circular-linear correlation In Directional: Directional Statistics

## Description

It calculates the squared correlation between a circular and one or more linear variables.

## Usage

 `1` ```circlin.cor(theta, x, rads = FALSE) ```

## Arguments

 `theta` The circular variable. `x` The linear variable or a matrix containing many linear variables. `rads` If the circualr variable is in rads, this should be TRUE and FALSE otherwise.

## Details

The squared correlation between a circular and one or more linear variables is calculated.

## Value

A matrix with as many rows as linear variables including:

 `R-squared` The value of the squared correlation. `p-value` The p-value of the zero correlation hypothesis testing.

## Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <[email protected]> and Giorgos Athineou <[email protected]>

## References

Mardia, K. V. and Jupp, P. E. (2000). Directional statistics. Chicester: John Wiley & Sons.

```circ.cor1, circ.cor2, spml.reg ```

## Examples

 ```1 2 3 4 5``` ```phi <- rvonmises(50, 2, 20, rads = TRUE) x <- 2 * phi + rnorm(50) y <- matrix(rnorm(50 * 5), ncol = 5) circlin.cor(phi, x, rads = TRUE) circlin.cor(phi, y, rads = TRUE) ```

### Example output

```     R-squared      p-value
[1,] 0.1726796 0.0002751809
R-squared    p-value
[1,] 0.02175827 0.35958670
[2,] 0.01060580 0.60744650
[3,] 0.02425365 0.31977265
[4,] 0.01485813 0.49738872
[5,] 0.08703993 0.01655189
```

Directional documentation built on March 19, 2018, 5:05 p.m.