Evaluation of a Multiplicative Generator of Pseudo-random Numbers PDF Download
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Author: Frederick W. Kuehl
Publisher:
ISBN:
Category : Random number generators
Languages : en
Pages : 36
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Book Description
Author: Frederick W. Kuehl
Publisher:
ISBN:
Category : Random number generators
Languages : en
Pages : 36
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Book Description
Author: Frederick W. Kuehl
Publisher:
ISBN:
Category :
Languages : en
Pages : 30
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Book Description
The present study reports on the development and testing of a pseudo-random number generator which would be able to rapidly supply the SIMPO-I entity models with numbers meeting essential tests for random qualities. The generator developed by BESRL is a power residue or multiplicative generator, the simplest of the many generators based on the linear congruential method. In addition to an acceptable generator, the work accomplished resulted in a compilation of statistical tests which have wider application for evaluating generators used on other computer systems. The tests are described, and essential mathematical formulations are presented. (Author).
Author:
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ISBN:
Category :
Languages : en
Pages : 0
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Book Description
The present study reports on the development and testing of a pseudo-random number generator which would be able to rapidly supply the SIMPO-I entity models with numbers meeting essential tests for random qualities. The generator developed by BESRL is a power residue or multiplicative generator, the simplest of the many generators based on the linear congruential method. In addition to an acceptable generator, the work accomplished resulted in a compilation of statistical tests which have wider application for evaluating generators used on other computer systems. The tests are described, and essential mathematical formulations are presented. (Author).
Author: SYSTEM DEVELOPMENT CORP SANTA MONICA CALIF.
Publisher:
ISBN:
Category :
Languages : en
Pages : 1
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Book Description
Two pseudo-random number generators are considered, the multiplicative congruential method and the mixed congruential method. Some properties of the generated sequences ar derived, and several algorithms are developed for the evaluation of x sub i = f(i) and i = f to the minus 1 power (x sub i), where x sub i is the i'th element of a pseudo-random number sequence. (Author).
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Category :
Languages : en
Pages :
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Book Description
To be effective, a linear congruential random number generator (LCG) should produce values that are (a) uniformly distributed on the unit interval (0,1) excluding endpoints and (b) substantially free of serial correlation. It has been found that many statistical methods produce inflated Type I error rates for correlated observations. Theoretically, independently seeding an LCG under the following conditions attenuates serial correlation: (a) simple random sampling of seeds, (b) non-replicate streams, (c) non-overlapping streams, and (d) non-adjoining streams. Accordingly, 4 algorithms (each satisfying at least 1 condition) were developed: (a) zero-leap, (b) fixed-leap, (c) scaled random-leap, and (d) unscaled random-leap. Note that the latter satisfied all 4 independent seeding conditions. To assess serial correlation, univariate and multivariate simulations were conducted at 3 equally spaced intervals for each algorithm (N=24) and measured using 3 randomness tests: (a) the serial correlation test, (b) the runs up test, and (c) the white noise test. A one-way balanced multivariate analysis of variance (MANOVA) was used to test 4 hypotheses: (a) omnibus, (b) contrast of unscaled vs. others, (c) contrast of scaled vs. others, and (d) contrast of fixed vs. others. The MANOVA assumptions of independence, normality, and homogeneity were satisfied. In sum, the seeding algorithms did not differ significantly from each other (omnibus hypothesis). For the contrast hypotheses, only the fixed-leap algorithm differed significantly from all other algorithms. Surprisingly, the scaled random-leap offered the least difference among the algorithms (theoretically this algorithm should have produced the second largest difference). Although not fully supported by the research design used in this study, it is thought that the unscaled random-leap algorithm is the best choice for independently seeding the multiplicative congruential random number generator. Accordingly, suggestions for f.
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Category :
Languages : en
Pages : 0
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Book Description
There exist today many 'good' pseudo-random number generators; the problem is to retrieve them. This document discusses three commonly used pseudo-random number generators, the first being RANDU, a notoriously bad generator, but one which is still occasionally used. The next is the widely used prime modulus, multiplicative congruential generator used in LL-RANDOMII, the Naval Postgraduate School random number package, and the last is the random number generator provided for microcomputers with the DOS operating system. This latter pseudo-random number generator is completely defective. Simple graphical methods for initial screening of pseudo-random number generators are given, and the problems which arise with bad pseudo-random number generators are detailed with graphics. Finally, recent work on obtaining even better pseudo-random number generators is discussed.
Author: Peter A. Lewis
Publisher:
ISBN:
Category :
Languages : en
Pages : 21
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Book Description
There exist today many 'good' pseudo-random number generators; the problem is to retrieve them. This document discusses three commonly used pseudo-random number generators, the first being RANDU, a notoriously bad generator, but one which is still occasionally used. The next is the widely used prime modulus, multiplicative congruential generator used in LL-RANDOMII, the Naval Postgraduate School random number package, and the last is the random number generator provided for microcomputers with the DOS operating system. This latter pseudo-random number generator is completely defective. Simple graphical methods for initial screening of pseudo-random number generators are given, and the problems which arise with bad pseudo-random number generators are detailed with graphics. Finally, recent work on obtaining even better pseudo-random number generators is discussed.
Author: Emma E. Brown
Publisher:
ISBN:
Category : Psychology
Languages : en
Pages : 68
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Author:
Publisher:
ISBN:
Category : Government publications
Languages : en
Pages : 1730
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Author: John Komo
Publisher: Elsevier
ISBN: 0323156274
Category : Technology & Engineering
Languages : en
Pages : 317
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Book Description
Random Signal Analysis in Engineering Systems
