Robust multivariate mean estimation: The optimality of trimmed mean

Estimation of the Multivariate Normal Mean under the Extended Reflected Normal Loss Function

Robust Estimation of Mean Values

In this paper, we develop a computational approach for estimating the mean value of a quantity in the presence of uncertainty. We demonstrate that, under some mild assumptions, the upper and lower bounds of the mean value are efficiently computable via a sample reuse technique, of which the computational complexity is shown to posses a Poisson distribution.

Application of robust multivariate control chart with Winsorized Mean: a case study

Water pH and active ingredient concentration are two of the most important variables to consider in the manufacturing process of fungicides. If these variables do not meet the required standards, the quality of the product may be compromised and lead to poor fungicide performance when water is used as the application carrier, which is in most cases. Given the correlation between the variable...

Finite Sample Tail Behavior of the Multivariate Trimmed Mean Based on Tukey-Donoho Halfspace Depth

Adaptive trimmed mean as a location estimate

Abstract The trimmed mean is one of the most common estimators of location for symmetrical distributions, whose effect depends on whether the trim rate matches the proportion of contaminated data. Based on the geometric characteristics of the curve of the trimmed variance function, the authors propose two kinds of adaptive trimmed mean algorithms. The accuracy of the estimators is compared with...