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Format: VoseModPERT(min, mode, max, g,
U)
David Vose developed a modification of the PERT distribution with minimum a, most likely b and maximum c to produce shapes with varying degrees of uncertainty for the a,b,c values by changing the assumption about the mean:
In the standard PERT, g = 4, which is the PERT network assumption that the best estimate of the duration of a task = (a + 4b + c) /6. However, if we increase the value of g, the distribution becomes progressively more peaked and concentrated around b (and therefore less uncertain). Conversely, if we decrease g the distribution becomes flatter and more uncertain. The figure below illustrates the effect of three different values of g for a modified PERT(5,7,10) distribution.
This modified PERT distribution can be very useful in modeling expert
opinion. The expert is asked to estimate the same three values as before
(i.e. minimum, most likely and maximum). Then the g
parameter is varied and the expert is asked to select the shape that fits
his/her opinion most accurately.
An alternative to the modified PERT distribution is the Beta
Subjective in which one explicitly specifies the mean of the distribution
as well as the min, mode and max.
VoseModPERT generates values from this distribution or calculates a percentile
VoseModPERT constructs a distribution object for this distribution
VoseModPERTProb returns the probability density or cumulative distribution function for this distribution
VoseModPERTProb10 returns the log10 of the probability density or cumulative distribution function
