Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1149940 | Journal of Statistical Planning and Inference | 2008 | 15 Pages |
Directional data often arise in many sciences, including astronomy, biology, ecology, geology and medicine. One particular statistical problem of interest is whether the data are from a mixture of two von Mises distributions or one single von Mises distribution. Motivating examples include a DNA microarray experiment, where it is suggested that a proportion of circadian genes have systematically different phase/peak expressions in two different tissues. We study the use of the modified likelihood ratio test (MLRT) to this class of problems. The MLRT statistic is shown to have a simple χ12 null limiting distribution. The result is extended to mixture models with general parametric kernels. The simulation study gives additional insight into the finite-sample performance of the test. Two real data examples are used to illustrate the proposed method.