A consistent multivariate test of association based on ranks of distances
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In this paper, the problem of detecting associations between random vectors of any dimension is considered and a powerful test that is applicable in all dimensions and consistent against all alternatives is proposed. But the test has a simple form, is easy to implement, and has good power.Abstract:
SUMMARY We consider the problem of detecting associations between random vectors of any dimension. Few tests of independence exist that are consistent against all dependent alternatives. We propose a powerful test that is applicable in all dimensions and consistent against all alternatives. The test has a simple form, is easy to implement, and has good power.read more
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Applied smoothing techniques for data analysis : the kernel approach with S-plus illustrations
Adrian Bowman,Adelchi Azzalini +1 more
TL;DR: 1. Density estimation for exploring data 2. D density estimation for inference 3. Nonparametric regression for explore data 4. Inference with nonparametric regressors 5. Checking parametric regression models 6. Comparing regression curves and surfaces