A frequency domain test for isotropy in spatial data models

we develop a new methodology for estimating and testing the form of anisotropiy of homogeneous spatial processes. We derive a generalized version of the isotropy test proposed by Arbvia ety al (2013) and analyse its propoerties in variius settings. Expanding on this we propose a new testing procedure in the frequency domain that allows one to estimate and test under mild conditions any form of anisotropy in homogenoues spatial processes. The power of the test is studied by means of Monte Carlo simulations performed both on regoular and irregularly spaced data. Finally the method is used to analyse soybean yelds in the US.