Efficient ANOVA for Directional Data
In this paper we tackle the ANOVA problem for directional data (with particular emphasison geological data) by having recourse to the Le Cam methodology usually reserved for linearmultivariate analysis. We construct locally and asymptotically most stringent parametric testsfor ANOVA for directional data within the class of rotationally symmetric distributions. We turnthese parametric tests into semi-parametric ones by (i) using a studentization argument (whichleads to what we call pseudo-FvML tests) and by (ii) resorting to the invariance principle (whichleads to e_cient rank-based tests). Within each construction the semi-parametric tests inheritoptimality under a given distribution (the FvML distribution in the _rst case, any rotationallysymmetric distribution in the second) from their parametric antecedents and also improve onthe latter by being valid under the whole class of rotationally symmetric distributions. Asymp-totic relative e_ciencies are calculated and the _nite-sample behavior of the proposed tests isinvestigated by means of a Monte Carlo simulation. We conclude by applying our _ndings on areal-data example involving geological data.
|Date of creation:||2013|
|Date of revision:|
|Publication status:||Published by:|
|Contact details of provider:|| Postal: |
Phone: (32 2) 650 30 75
Fax: (32 2) 650 44 75
Web page: http://difusion.ulb.ac.be
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:eca:wpaper:2013/134946. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Benoit Pauwels)
If references are entirely missing, you can add them using this form.