On confidence intervals for the coherence function

We address the problem of confidence interval estimation for the coherence function. We revisit a recently proposed approach to calculate confidence intervals from the asymptotic distribution function of the sample coherence function. We then propose a bootstrap based approach and compare the level of confidence obtained by the two methods as well as a well-established method proposed by Enochson and Goodman (1965). Extensive simulations have shown that the bootstrap approach is more accurate, in particular for a large coherence and non-Gaussian data.