Optimized estimates of the regularity of the conditional distribution of the sample mean

We give an improved estimate for the regularity of the conditional distribution of the empiric mean of a finite sample of IID random variables, conditional on the sample "fluctuations", extending the well-known property of Gaussian IID samples. Specifically, we replace the bounds in probability, established in our earlier works, by those in distribution, and this results in the optimal regularity exponent in the final estimate.Comment: arXiv admin note: substantial text overlap with arXiv:1304.691

On the regularity of the conditional distribution of the sample mean

We show that the hypothesis of regularity of the conditional distribution of the empiric average of a finite sample of IID random variables, given all the sample "fluctuations", which appeared in our earlier manuscript |1] in the context of the eigenvalue concentration analysis for multi-particle random operators, is satisfied for a class of probability distributions with piecewise-constant or sufficiently smooth probability density. It extends the well-known property of Gausssian IID samples