AMRandom 4.3 free download AMRandom is a Delphi translation of Alan Miller's Random Module for FORTRAN. Supplies several different distributions of random numbers including Normal, Poisson, Gamma, etc. Includes Full Delphi Source and Demo   
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AMRandom 4.3    View screenshot )


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AMRandom is a Delphi translation of Alan Miller's Random Module for FORTRAN. Supplies several different distributions of random numbers including Normal, Poisson, Gamma, etc. Includes Full Delphi Source and Demo

Updated Dec 26, 2011 12:06:39
Rating    16 ( -2 -12.5% )
Size437 kb
LicenceFreeware
StatusMinor Update
LanguagesEnglish
OSWindows 98, Windows 2000, Windows XP, Windows Vista
Homepageesbconsult.com
AuthorGlenn Crouch
AMRandom 4.3 free download AMRandom is a Delphi translation of Alan Miller's Random Module for FORTRAN. Supplies several different distributions of random numbers including Normal, Poisson, Gamma, etc. Includes Full Delphi Source and Demo

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Description:
   This aims to supply an Embarcadero (formerly CodeGear/Borland) Delphi translation of Alan Miller's Random Module for FORTRAN-90. This translation has been done with Dr Miller's approval and is being made FREELY available to all Delphi Developers, though we do ask the Alan Miller and ESB Consultancy be given due credit.

   It includes the following Random Number Generators:

   - Normal (Gaussian)

   - Gamma

   - Chi-squared

   - Exponential

   - Weibull

   - Beta

   - t

   - Multivariate Normal

   - Generalized inverse Gaussian

   - Binomial (2 different ones)

   - Negative Binomial

   - von Mises

   - Cauchy

   -Lognormal

   Includes full Delphi Source and Demo.
Short tags:
Delph, Random, Math, Mathematics, Stats, Statistics, Random Numbers, Normal, Poisson, Gaussian, Lognormal
System Requirements:
Borland/CodeGear Delphi 5 or better
Change Info:
Support for Embarcadero Delphi 2010
find all version  Find last version of AMRandom
Free Download now  Free Download AMRandom 4.3 from esbconsult.com

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Home > Software > Development Tools > Delphi > download now AMRandom

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