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SeMIS is a multiple importance sampling (MIS)–based Bayesian inference algorithm designed for multimodal and high-dimensional posterior distributions. The algorithm constructs a sequence of softly ...
Coherent interleaved sampling is a new technique that can acquire data faster with more data points than sequential sampling. Engineers who need to characterize semiconductor devices, high-speed ...
Abstract: We study a ranking and selection problem with exponential sampling distributions. Under a Bayesian framework, we derive the posterior distribution of the performance parameter, and provide a ...
Understanding the statistics of extreme events in dynamical systems of high complexity is of vital importance for reliability assessment and design. We formulate a method to pick samples optimally so ...
If you specify the option METHOD=SEQ and do not include a SIZE statement, PROC SURVEYSELECT uses the equal probability version of Chromy's method for sequential random sampling. This method selects ...
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