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- W3185364777 abstract "In 2016, Karney proposed an exact sampling algorithm for the standard normal distribution. In this paper, we study the computational complexity of this algorithm under the random deviate model. Specifically, Karney’s algorithm requires the access to an infinite sequence of independently and uniformly random deviates over the range (0, 1). We give a theoretical estimate of the expected number of uniform deviates used by this algorithm until it completes, and present an improved algorithm with lower uniform deviate consumption. The experimental results also shows that our improved algorithm has better performance than Karney’s algorithm." @default.
- W3185364777 created "2021-08-02" @default.
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- W3185364777 date "2021-07-28" @default.
- W3185364777 modified "2023-10-10" @default.
- W3185364777 title "An improved exact sampling algorithm for the standard normal distribution" @default.
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- W3185364777 doi "https://doi.org/10.1007/s00180-021-01136-w" @default.
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