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From Frontline Systems, developers of the Excel Solver.

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Learn to use optimization for resource allocation, and Monte Carlo simulation for risk analysis of your model.


 

Risk Solver Engine - Sampling Methods and Distribution Functions

Sampling Methods and Distribution Functions

Risk Solver Engine can generate Monte Carlo samples from a wide range of probability distributions, using any of three methods:

  • Standard Monte Carlo
  • Latin Hypercube
  • Sobol Numbers

Sobol numbers are an innovation in Risk Solver Engine that's not found in other software for Monte Carlo simulation.  They are widely used by developers in quantitative finance.  For low to moderate dimensional problems, Sobol numbers offer the "best of both worlds" -- the speed of Standard Monte Carlo with the "coverage" of Latin Hypercube sampling.

Risk Solver Engine provides both a complete set of analytic probability distributions, and a complete set of methods for defining custom distributions, both discrete and continuous, by supplying sample data or by specifying certain parameters.  And you can specify shifting and truncation to customize your probability distributions.

Continuous Analytic Distributions

PsiBeta

PsiLaplace

PsiPareto2

PsiBetaGen

PsiLogistic

PsiPearson5

PsiBetaSubj

PsiLogLogistic

PsiPearson6

PsiCauchy

PsiLogNormal

PsiPert

PsiChiSquare

PsiLogNorm2

PsiRayleigh

PsiErf

PsiMaxExtreme

PsiStudent

PsiErlang

PsiMinExtreme

PsiTriangGen

PsiExponential

PsiMyerson

PsiTriangular

PsiGamma

PsiNormal

PsiUniform

PsiInvNormal

PsiPareto

PsiWeibull

Discrete Analytic Distributions

PsiBernoulli

PsiHyperCeo

PsiNegBinomial

PsiBinomial

PsiIntUniform

PsiPoisson

PsiGeometric

PsiLogarithmic

  

Custom and Special Distributions

PsiCumul

PsiHistogram

PsiShuffle

PsiDiscrete

PsiMVLogNormal

PsiSip

PsiDisUniform

PsiMVNormal

PsiSlurp

PsiGeneral

PsiResample

PsiCertified

If you are programming in Excel VBA, you can easily create an instance of a Distribution object, with the properties of any of these probability distributions.  By simply accessing properties of this object, you can obtain the probability density (PDF) or cumulative density (CDF) function, or analytic values for the moments of the distribution, based on its type and parameters.

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