Dual-type quantile regression approach for mean estimation incorporating sampled and non-sampled data
Dual-type quantile regression approach for mean estimation incorporating sampled and non-sampled data
Drawing inspiration from recent advancements in robust mean estimation within finite sampling theory, we introduce a novel dual-type class of mean estimators in a design-based framework. The dual-type class is based on quantile regression and is specifically designed to be effective in the presence of extreme observations. Significantly, it integrates …