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Abstract
This article is an expansion of G. E. Forsythe’s paper “Von Neumann’s comparison method for random sampling from the normal and other distributions” [5]. It is shown that Forsythe’s method for the normal distribution can be adjusted so that the average number N of uniform deviates required drops to 2.53947 in spite of a shorter program. In a further series of algorithms, N is reduced to values close to 1 at the expense of larger tables. Extensive computational experience is reported which indicates that the new methods compare extremely well with known sampling algorithms for the normal distribution.
Original language | English |
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Pages (from-to) | 927-937 |
Journal | Mathematics of Computation |
Volume | 27 |
Issue number | 124 |
DOIs | |
Publication status | Published - 1973 |
Treatment code (Nähere Zuordnung)
- Basic - Fundamental (Grundlagenforschung)
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