| circ.cor {CircStats} | R Documentation |
Correlation Coefficient for Angular Variables
Description
Computes a circular version of the Pearson's product moment correlation, and performs a significance test if requested.
Usage
circ.cor(alpha, beta, test=FALSE)
Arguments
alpha |
vector of circular data measured in radians. |
beta |
vector of circular data measured in radians. |
test |
if test = TRUE, then a significance test for the correlation coefficient is computed. |
Details
The correlation coefficient is computed like Pearson's product moment correlation for two linear variables X and Y. In the computational formula, however, (xi - xbar) and (yi - ybar) are replaced by sin(xi - xbar) and sin(yi - ybar), where xbar and ybar in the second two expressions are the mean directions of the samples.
Value
Returns a data frame with variables r, a circular version of the Pearson's product moment correlation, test.stat and p.value, the test statistic and p-value respectively, for testing significance of the correlation coefficient. test.stat and p.value are by default not produced, but are given when test=TRUE is specified in the function call.
References
Jammalamadaka, S. Rao and SenGupta, A. (2001). Topics in Circular Statistics, Section 8.2, World Scientific Press, Singapore.
Jammalamadaka, S. and Sarma, Y. (1988). A correlation coefficient for angular variables. Statistical Theory and Data Analysis 2. North Holland: New York.
Examples
# Generate two circular data sets, and compute their correlation.
data1 <- rvm(50, 0, 3)
data2 <- data1 + pi + rvm(50, 0, 10)
circ.cor(data1, data2, test=TRUE)