rayleigh.test: Rayleigh Test of Uniformity

In circular: Circular Statistics

Description

Performs a Rayleigh test of uniformity, assessing the significance of the mean resultant length. The alternative hypothesis is a unimodal distribution with unknown mean direction and unknown mean resultant length if mu is NULL otherwise the alternative hypothesis is a unimodal distribution with a specified mean direction and unknown mean resultant length.

Usage

rayleigh.test(x, mu = NULL)
## S3 method for class 'rayleigh.test'
print(x, digits=4, ...)

Arguments

x	a vector. The object is coerced to class circular.
mu	Specified mean direction in alternative hypothesis as a circular object.
digits	integer indicating the precision to be used.
...	further arguments passed to or from other methods.

Value

Returns a list with three components: the mean resultant length, statistic, the p-value of the test statistic, p.value and the value of the alternative mean direction mu.

Author(s)

Claudio Agostinelli and Ulric Lund

References

Jammalamadaka, S. Rao and SenGupta, A. (2001). Topics in Circular Statistics, Sections 3.3.2 and 3.4.1, World Scientific Press, Singapore.

See Also

range.circular, kuiper.test, rao.spacing.test and watson.test

Examples

x <- rvonmises(n=25, mu=circular(pi), kappa=2)
# General alternative
rayleigh.test(x)
# Specified alternative
rayleigh.test(x, mu=circular(0))

Example output

Attaching package: 'circular'

The following objects are masked from 'package:stats':

    sd, var


       Rayleigh Test of Uniformity 
       General Unimodal Alternative 

Test Statistic:  0.5242 
P-value:  7e-04 


       Rayleigh Test of Uniformity 
       Alternative with Specified Mean Direction:  0 

Test Statistic:  -0.5217 
P-value:  0.9999 

circular documentation built on May 2, 2019, 4:42 p.m.