mytest > help > Part 2. MM4XL Tools > 1. Strategic Tools > Risk Analyst > 4. Functions > 3. Distribution Functions > mmERF(Mean)

Risk Analyst

mmERF(Mean)

Example

=mmERF(1) can equal -1.231669545

Application

The Error Function, also called Erf, is used to calculate failure times in engineering, mortality in population biology, event histories in sociology, and more. It looks like the Normal distribution, but it assigns more importance to extreme values than the Normal one does.

How to use

This formula returns extreme values. Say we are working on short-term sales levels and we are modeling forecast errors as computed with the Forecast Manager tool of MM4XL software (refer to the example file Forecast Manager.xls, sheet MM4XL Forecast, range L33:L90). The formula below may be used to simulate the errors produced with the times series of the forecast example:

=mmERF(0.1276)

The Mean level for the formula above has been found using the Fitting tool with the data in range L33:L90, yet this is the same mean value that one can find in cell H17.

Copy the formula above in 100 cells. You will find that most simulated values will range, roughly speaking, within plus or minus 15%, whilst the actual error terms produced with Forecast Manager range from -9.5% to 10.6% (in the example file mentioned above see cells H16 and H20, respectively).

Technical profile

Type Continuous distribution.
Syntax =mmERF(Mean)
Domain  Monte Carlo Simulation Software: Management Process Risk Analysis.
Mode 0
Parameters Mean is the location parameter.
Remarks If the Mean is nonnumeric mmERF returns the #VALUE! error value.
Relationships It is related to the Normal and to the Uniform variates.
Graphs
mmERF(1) mmERF(10)
 Monte Carlo Simulation Software: Management Process Risk Analysis  Monte Carlo Simulation Software: Management Process Risk Analysis
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