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Weighted average importance sampling and defensive mixture distributions. (English) Zbl 0822.62002
Summary: Importance sampling uses observations from one distribution to estimate for another distribution by weighting the observations. Including the target distribution as one component of a mixture distribution bounds the weights and makes importance sampling more reliable. The usual importance-sampling estimate is a weighted average with weights that do not sum to 1. We discuss simple normalization and other, more efficient normalization methods. These innovations make importance sampling useful in a wider variety of problems. We demonstrate with a case study of oil- inventory reliability at a large utility.

MSC:
62D05 Sampling theory, sample surveys
90B05 Inventory, storage, reservoirs
62P99 Applications of statistics
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