Accurate inference for a one parameter distribution based on the mean of a transformed sample
Methodology
2010-09-14 v1
Abstract
A great deal of inference in statistics is based on making the approximation that a statistic is normally distributed. The error in doing so is generally and can be very considerable when the distribution is heavily biased or skew. This note shows how one may reduce this error to , where is a given integer. The case considered is when the statistic is the mean of the sample values from a continuous one-parameter distribution, after the sample has undergone an initial transformation.
Cite
@article{arxiv.1009.2190,
title = {Accurate inference for a one parameter distribution based on the mean of a transformed sample},
author = {C. S. Withers and S. Nadarajah},
journal= {arXiv preprint arXiv:1009.2190},
year = {2010}
}