Description Usage Arguments Details Value Author(s) References Examples
View source: R/watson.two.test.R
Performs Watson's test for homogeneity on two samples of circular data.
1 2 3  watson.two.test(x, y, alpha=0)
## S3 method for class 'watson.two.test'
print(x, digits=4, ...)

x 
a vector. The object is coerced to class

y 
a vector. The object is coerced to class

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 pvalue will be returned. 
digits 
integer indicating the precision to be used. 
... 
further arguments passed to or from other methods. 
Watson's twosample test of homogeneity is performed, and the results are printed. If alpha is specified and nonzero, 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 pvalue of the test is given.
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 pvalues 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.
a list with statistic, alpha and the number of observations of the first and second sample.
Claudio Agostinelli and Ulric Lund
Jammalamadaka, S. Rao and SenGupta, A. (2001). Topics in Circular Statistics, Section 7.5, World Scientific Press, Singapore.
1 2 3 4 5 6  # Perform a twosample test of homogeneity on two
# simulated data sets.
data1 < rvonmises(n=20, mu=circular(0), kappa=3)
data2 < rvonmises(n=20, mu=circular(pi), kappa=2)
watson.two.test(data1, data2, alpha=0.05)
watson.two.test(data1, data2)

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