Projections based test of uniformity {Directional}

Projections based test of uniformity

Description

It checkes whether the data are uniformly distributed on the circle or the (hyper-)sphere.

Usage

ptest(x, B = 100)

Arguments

x

A matrix containing the data, unit vectors.

B

The number of random uniform projections to use.

Details

For more details see Cuesta-Albertos, Cuevas and Fraiman (2009).

Value

A list including:

pvalues

The p-values of the Kolmogorov-Smirnov tests.

pvalue

The p-value of the test based on the Benjamini and Heller (2008) procedure.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

References

Cuesta-Albertos J. A., Cuevas A. and Fraiman, R. (2009). On projection-based tests for directional and compositional data. Statistics and Computing, 19: 367–380.

Benjamini Y. and Heller R. (2008). Screening for partial conjunction hypotheses. Biometrics, 64(4): 1215–1222.

See Also

rayleigh, kuiper

Examples

x <- rvmf(100, rnorm(5), 1)  ## Fisher distribution with low concentration
ptest(x)