Efficient sampling when the inclusion probabilities do not sum to an integer
(English)Manuscript (preprint) (Other academic)
Usually when sampling with unequal inclusion probabilities a fixed sample size is desirable. Then it is required that the sum of the inclusion probabilities should equal the sample size. Sometimes it is not suitable to re-scale the inclusion probabilities to sum to an integer. It is shown that every unequal probability sampling design for fixed sample size can be extended to this situation. The cost for not re-scaling the inclusion probabilities is that we have to accept a small variation in sample size. Different strategies for estimation under these circumstances are also given.
conditional inclusion probabilities, extended Sampford sampling, Horvitz-Thompson estimator, ratio estimator, unequal probability sampling
Probability Theory and Statistics
Research subject Mathematical Statistics
IdentifiersURN: urn:nbn:se:umu:diva-33699OAI: oai:DiVA.org:umu-33699DiVA: diva2:317393