watson.two {CircStats}

Watson's Two-Sample Test of Homogeneity

Description

Performs Watson's test for homogeneity on two samples of circular data.

Usage

watson.two(x, y, alpha=0, plot=FALSE)

Arguments

x

vector of circular data measured in radians.

y

vector of circular data measured in radians.

alpha

significance level of the test. Valid levels are 0.001, 0.01, 0.05, 0.1. This argument may be ommited, in which case, a range for the p-value will be returned.

plot

logical value. If TRUE, an overlayed plot of both empirical distribution functions will be sent to the current graphics device. The default value if FALSE.

Details

Critical values for the test statistic are obtained using the asymptotic distribution of the test statistic. It is recommended to use the obtained critical values and ranges for p-values only for combined sample sizes in excess of 17. Tables are available for smaller sample sizes and can be found in Mardia (1972) for instance.

Value

NULL

Note

Watson's two-sample test of homogeneity is performed, and the results are printed to the screen. If alpha is specified and non-zero, the test statistic is printed along with the critical value and decision. If alpha is omitted, the test statistic is printed and a range for the p-value of the test is given. If plot=TRUE, an overlayed plot of both empirical distribution functions will be sent to the current graphics device.

References

Jammalamadaka, S. Rao and SenGupta, A. (2001). Topics in Circular Statistics, Section 7.5, World Scientific Press, Singapore.

Examples

# Perform a two-sample test of homogeneity on two
# simulated data sets.
data1 <- rvm(20, 0, 3)
data2 <- rvm(20, pi, 2)
watson.two(data1, data2, alpha=0.05, plot=TRUE)
watson.two(data1, data2)