Bootstrap 2-sample mean test for circular data.
hcfcirc.boot(u1, u2, rads = TRUE, B = 999)
lrcirc.boot(u1, u2, rads = TRUE, B = 999)
hclrcirc.boot(u1, u2, rads = TRUE, B = 999)
embedcirc.boot(u1, u2, rads = TRUE, B = 999)
hetcirc.boot(u1, u2, rads = TRUE, B = 999)This is an "htest"class object. Thus it returns a list including:
The test statistic value.
The degrees of freedom of the test. Since these are bootstrap based tests this is "NA".
The p-value of the test.
A character with the alternative hypothesis.
A character with the test used.
A character vector with two elements.
A numeric vector containing the data of the first sample.
A numeric vector containing the data of the first sample.
If the data are in radians, this should be TRUE and FALSE otherwise.
The number of bootstraps to perform.
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
The high concentration (hcfcirc.boot), the log-likelihood ratio test (lrcirc.boot), high concentration log-likelihood ratio (hclrcirc.boot), embedding approach (embedcirc.boot), or the non equal concentration parameters approach (hetcirc.boot) is used.
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.
Tsagris M. and Alenazi A. (2024). An investigation of hypothesis testing procedures for circular and spherical mean vectors. Communications in Statistics-Simulation and Computation, 53(3): 1387--1408.
hcf.circaov, hcfcircboot, het.aov
u1 <- rvonmises(20, 2.4, 5)
u2 <- rvonmises(20, 2.4, 10)
hcfcirc.boot(u1, u2)
Run the code above in your browser using DataLab