An alternative to Poisson sampling called Sunter sampling is introduced into the forestry literature. The probability of selecting a sample unit depends on its size and the number of previous units selected as well as on the sizes and number of units remaining in the population. This results in a less variable sample size than in Poisson sampling. Sunter sampling is more efficient than Poisson sampling where a sampling list is available prior to sampling if a slightly biased adjusted estimator similar to one in Poisson sampling is used. Approximate true variances are given for both the unadjusted and adjusted estimators. Two sample-based variance approximations provide reliable estimates of both the true and simulation variance of the adjusted estimator. Sunter sampling is not yet a practical alternative when no sampling list is available but perhaps could be an alternative to, for example, point-Poisson sampling.A new sampling scheme is introduced that could be quite efficient in timber sales and other inventories. Some of these inventories currently suffer from random sample sizes which may result in inventories being more costly or less precise than planned for. The study suggests applications where this new method may be useful.
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