Permutation based 2-sample mean test for circular data
Permutation based 2-sample mean test for circular data.
hcfcirc.perm(u1, u2, rads = TRUE, B = 999) hetcirc.perm(u1, u2, rads = TRUE, B = 999) lrcirc.perm(u1, u2, rads = TRUE, B = 999) hclrcirc.perm(u1, u2, rads = TRUE, B = 999) embedcirc.perm(u1, u2, rads = TRUE, B = 999)
u1 |
A numeric vector containing the data of the first sample. |
u2 |
A numeric vector containing the data of the first sample. |
rads |
If the data are in radians, this should be TRUE and FALSE otherwise. |
B |
The number of permutations to perform. |
The high concentration (hcfcirc.perm), log-likelihood ratio (lrcirc.perm), high concentration log-likelihood ratio (hclrcirc.perm), embedding approach (embedcirc.perm) or the non equal concentration parameters approach (hetcirc.perm) is used.
A vector including:
test |
The value of the test statistic. |
p-value |
The p-value of the test. |
kappa |
The concentration parameter based on all the data. If the het.circaov is used this argument is not returned. |
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
Mardia, K. V. and Jupp, P. E. (2000). Directional statistics. Chicester: John Wiley & Sons.
Rumcheva P. and Presnell B. (2017). An improved test of equality of mean directions for the Langevin-von Mises-Fisher distribution. Australian & New Zealand Journal of Statistics, 59(1), 119-135.
u1 <- rvonmises(20, 2.4, 5) u2 <- rvonmises(20, 2.4, 10) hcfcirc.perm(u1, u2) lrcirc.perm(u1, u2)
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