Abstract
We introduce variance reduction techniques as general tools for estimating probabilities from invariant permutation distributions. The paper discusses importance sampling, antithetic sampling and control variates sampling as alternatives to uniform Monte Carlo sampling for estimating exact critical values orP-values in a broad class of permutation tests. Results may be extended to permutation confidence intervals and linear rank tests. An asymptotic theory is provided for each proposed variance reduction method.
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