A geometric approach to finite sample and large deviation properties in two-way ANOVA with spherically distributed error vectors

This article investigates a two-way ANOVA model with interactions assuming that the vector of error variables possesses a general spherically symmetric distribution instead of a multivariate normal one. Via a geometric approach the authors study a test for the usual hypothesis of non-interaction under this general assumption. Moreover, based on a certain geometric representation formula, they establish exponential large deviation rates of the least squares estimators in the above model for a specific class of spherical distributions.