Nonparametric Optimal Tests for Independence in the Elliptical VAR Model
نویسندگان
چکیده
In this work we construct a class of locally asymptotically most stringent (in the Le Cam sense) tests for independence between two sets of variables in the VAR models. These tests are based on multivariate ranks of distances and multivariate signs of the observations and are shown to be asymptotically distribution-free under very mild assumptions on the noise, which is obtained by applying a linear transformation to a block of spherical innovation. The class of tests derived is invariant with respect to the group of block affine transformations and asymptotically invariant with respect to the group of continuous monotone marginal radial transformations.
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