This example explains how to use the RiskPert function.
Resources
The RiskSplice function lets you splice two distributions together at some point. This example shows how to use it.
The RiskStudent, RiskChiSq and RiskFfunctions can be used to simulate values from the three corresponding distributions commonly used in statistical inference: the Student's t, chi-square, and F distributions. You could simulate values from any of these distributions, just like you can simulate values from any other distribution. This example shows how to use them.
The RiskTriang, RiskTrigen and RiskDoubleTriang functions are used for modeling a continuous uncertain quantity that must be between specified minimum and maximum values. This example explains the main differences between them.
The RiskUniform function generates a value that is equally likely to be anywhere between specified minimum and maximum values. This example shows how to use it.
The RiskVary function is intended primarily for sensitivity analysis is @RISK's companion product, TopRank, but it is included in @RISK for compatibility with TopRank. You can use the RiskVary function in @RISK, but it provides no advantage over the "regular" @RISK distribution functions.
This model uses @RISK to illustrate that when several people with different prior beliefs all see the same random outcomes and use Bayes' rule to update their beliefs, they will all converge to the same "truth" in the long run.
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This model uses @RISK simulation to find the distribution of the number of events in a fixed amount of time when the times between events are independent and identically distributed random variables.
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This model illustrates how the central limit theorem can be used instead of the RiskCompound function when an output is the sum of a random number of random terms that might be correlated._x000D_
