Abstract
This paper considers the estimation of a quantity from a set of repeated measurements {xi} by the value of t minimizing ∑i |xi − t|p, as in Pennecchi and Callegaro (2006 Metrologia 43 213–19). The estimate with p = 2 is the familiar sample mean. Assumptions that are relevant when preferring an estimate with p < 2 are identified and examined. Theoretical considerations and results of simulations weaken the case for choosing an estimate with p < 2. The simulation results support the regular use of the sample mean or an estimate that involves the value p = 1.5 when the kurtosis of the dataset is sufficiently large.
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