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Abstract
K.R.W. Brewer suggests that when estimating the total of a single item for which there is control
(auxiliary) data, one employ a ratio or regression estimator and draw the sample using probabilities
proportional to the control values raised to a power between 1/2 and 1. Brewer's sample selection
scheme can be expanded to multiple targets by drawing overlapping Poisson samples for a number of
items simultaneously using permanent random numbers (PRN's). W e can call the result an example
of "Maximal Brewer Selection" (MBS). This paper develops the theory behind MBS and the
calibration estimator rendering it practical. It goes on to describe ho w this estimation strategy is being
used at the National Agricultural Statistics Service.