dcor.circular {CircMLE} R Documentation

## circular distance correlation function

### Description

Perform a distance correlation between circular datasets or between circular and linear datasets.

### Usage

dcor.circular(x, y, method = "chord", type = "c-c", ...)


### Arguments

 x A vector of class 'circular', or numeric vector of angles measured in radians y A vector of class 'circular', numeric vector of angles measured in radians, or numeric vector method the distance measure to be used. This must be one of the following functions: ‘"angularseparation"’, ‘"chord"’, '"geodesic"’, or '"circ.range"' (default = "chord"). see ?dist.circular for additional details. type if ‘type == "c-c"’ then perform a circular-circular distance corellation, else if ‘type == "c-l"’ then perform a circular-linear distance corellation (default = "c-c"). ... additional parameters passed to the dcor.test function

### Value

Same as from the dcor.test function: a list with class ‘htest’containing

method: description of test

statistic: observed value of the test statistic

estimate: dCov(x,y) or dCor(x,y)

estimates: a vector: [dCov(x,y), dCor(x,y), dVar(x), dVar(y)]

replicates: replicates of the test statistic

p.value: approximate p-value of the test

n: sample size

data.name: description of data

dcor dcov DCOR dcor.test dist.circular

### Examples

# Circular-circular distance corellation
x <- circular::rvonmises(n = 50, mu = circular::circular(0), kappa = 3)
y <- x + circular::rvonmises(n = 50, mu = circular::circular(pi), kappa = 10)
dcor.circular(x, y)

# Run permutation test with 9999 iterations
dcor.circular(x, y, R = 9999)

# Circular-linear distance corellation
x <- circular::rvonmises(n = 50, mu = circular::circular(0), kappa = 3)
y <- as.numeric(x) + rnorm(50, mean = 5, sd = 2)
dcor.circular(x, y, type = "c-l", R = 9999)


[Package CircMLE version 0.3.0 Index]