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Functions that generate random values from probability distributions.

 

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Beta
Beta

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titleBeta

Returns values from a Beta distribution.

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titleCustom

With Crystal Ball's Custom Distribution you can represent six different distributions, all of which are described here:

1. Discrete Uniform

2. Discrete

3. General

4. Histogram

5. Cumulative Ascending

6. Combination of distributions

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DiscreteUniform
DiscreteUniform

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titleDiscrete Uniform

Returns integer values between a specified minimum and maximum, all with the same probability (the Integer Uniform distribution). Discrete Uniform distribution can be constructed with the Custom Distribution in Crystal Ball. 

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titleExponential

Returns values from an Exponential distribution.

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ExtremeValue
ExtremeValue

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titleExtremeValue

Returns values from a Gumbel distribution for maximum observations. This is one of three Extreme Value distributions.

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Gamma
Gamma

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titleGamma

Returns values from a Gamma distribution.

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Geometric
Geometric

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titleGeometric

Returns values from a Geometric distribution. 

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Hypergeometric
Hypergeometric

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titleHypergeometric

 Returns values from a hypergeometric distribution.

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Logistic
Logistic

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titleLogistic

 Returns values from a Logistic distribution.

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Lognormal
Lognormal

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titleLognormal

 Returns values from a Lognormal distribution.

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MaximumExtreme
MaximumExtreme

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titleMaximumExtreme

Returns values from a Gumbel distribution for maximum observations. This is one of three Extreme Value distributions.

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MinimumExtreme
MinimumExtreme

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titleMinimumExtreme

Returns values from a Gumbel distribution for minimum observations. This is one of three Extreme Value distributions.

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Negbinomial
Negbinomial

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titleNegbinomial

Returns values from a Negative Binomial distribution. 

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Normal
Normal

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titleNormal

 Returns values from a Normal distribution.

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Pareto
Pareto

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titlePareto

Returns values from a Pareto distribution.

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Poisson
Poisson

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titlePoisson

 Returns values from a Poisson distribution.

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Student
Student

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titleStudent

 Returns values from a Student, or t- distribution (can also construct it in two other ways).

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Triangular
Triangular

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titleTriangular

 Returns values from a Triangle distribution.

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Uniform
Uniform

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titleUniform

Returns values from a Uniform distribution. 

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Weibull
Weibull

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titleWeibull

 Returns values from a Weibull distribution.


 

2. Crystal Ball Tools

Crystal Ball Tools are programs that extend the functionality of Crystal Ball. They are ordered in two categories:

Setup Tools

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BatchFit
BatchFit

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titleBatch Fit

The Batch Fit tool lets you "automatically" fit (continuous) probability distributions to multiple data series. At Epix Analytics, we don't use this tool often because fitting distributions to data should be done carefully (e.g. often one by one) and not always be based on just one of the available Goodness of Fit Statistics

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CorrelationMatrix
CorrelationMatrix

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titleCorrelation Matrix

The Correlation Matrix lets you enter a matrix of correlations between assumptions in one step. In the section about Rand Order Correlation, you can see how to use this tool. 

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TornadoChart
TornadoChart

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titleTornado Chart

The Tornado Chart Tool allows you to determine the impact of each model variable (one at a time) on one specific forecast. In the section about Spider Charts and the Tornado Chart tool, you can read how to use this tool.


Analysis Tools

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Bootstrap
Bootstrap

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titleBootstrap

The Bootstrap Tool of Crystal Ball is a special case of the more general Bootstrap method discussed in ModelAssist Advanced. Crystal Ball's Bootstrap tool looks at  how robust your  simulation forecast statistics are. For example, given that you have done 10,000  iterations, the Bootstrap Tool determines how precisely the forecast statistics have been determined, meaning by how much would those statistics change if one were to run an essentially infinite number of iterations. Therefore, the main use of the  Crystal Ball's Bootstrap Tool is to determine if you have run sufficient iterations. In contrast, the Bootstrap method discussed in ModelAssist Advanced helps you quantify the uncertainty you have about input parameters in your risk analysis model that have been estimated from data .

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DecisionTable
DecisionTable

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titleDecision Table

The Decision Table tool allows you to run multiple simulations to test different values of one or two decision variables. Here, you can see how this tool can be used, with an example model. The model Image RemovedImage AddedMarket growth model provides another example.

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ScenarioAnalysis
ScenarioAnalysis

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titleScenario Analysis

The Scenario Analysis Tool allows you to examine which combination of assumption values gives you a certain forecast result. The tool runs a simulation after which it matches all the forecasts with their corresponding assumption values. In the resulting table, it shows all the forecast values in the range you specified (e.g. between 95% and 100% percentile) sorted, along with all the corresponding assumption (input) values. This tool can therefore be used as one of the methods to get a better understanding of an output of a simulation. 

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TwodimensionalSimulation
TwodimensionalSimulation

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titleTwo dimensional Simulation

 The Two-Dimensional Simulation Tool in Crystal Ball lets you separate the effect of uncertainty (lack of knowledge) and variability and randomness in a forecast. For a more detailed descriptions, see here.

3. Statistics functions

Functions that report the simulation results within Excel cells. Although not always fully supported by Crystal Ball, these functions are very useful, in combination with on-screen recalculation, to monitor some aspect of the simulation. They are also useful for automatically producing reports in Excel, though this can slow down your models.

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titleCB.GetForeStatFN(x,2) - mean

CB.GetForeStatFN(source,2) reports the mean of the mean of the values generated for the source (cell reference, cell name or output name) so far in the simulation.

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titleCB.GetForeStatFN(x,7) - skewness

CB.GetForeStatFN(source,7) reports the Skewness of the values generated for the source (cell reference, cell name or output name) so far in the simulation.

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CB.GetForeStatFN(x,8)
CB.GetForeStatFN(x,8)

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titleCB.GetForeStatFN(x,8) - kurtosis

CB.GetForeStatFN(source,8) reports the kurtosis of the values generated for the source (cell reference, cell name or output name) so far in the simulation.

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titleCB.IterationsFN - Iteration

 CB.IterationsFN() reports the current iteration of the simulation when running.