RIS ID
87194
Abstract
Recently proposed outlier robust small area estimators can be substantially biased when outliers are drawn from a distribution that has a different mean from that of the rest of the survey data. This naturally leads one to consider an outlier robust bias correction for these estimators. We develop this idea, proposing two different analytical mean-squared error estimators for the ensuing bias-corrected outlier robust estimators. Simulations based on realistic outlier-contaminated data show that the bias correction proposed often leads to more efficient estimators. Furthermore, the mean-squared error estimation methods proposed appear to perform well with a variety of outlier robust small area estimators.
Grant Number
ARC/LP0776810
Publication Details
Chambers, R., Chandra, H., Salvati, N. & Tzavidis, N. (2014). Outlier robust small area estimation. Journal of the Royal Statistical Society Series B: Statistical Methodology, 76 (1), 47-69.