Description Usage Arguments Details Value Examples
((just an example extracted from the mc2d package to illustrate the use
of reduced documentation with a series of related and aliased functions.))
Density, distribution function, quantile function and random generation
for the PERT (aka Beta PERT) distribution with minimum equals to min, mode equals to mode
and maximum equals to max.
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x,q |
Vector of quantiles. |
p |
Vector of probabilities. |
n |
Number of observations. If length(n) > 1, the length is taken to be the number required. |
min |
Vector of minima. |
mode |
Vector of modes. |
max |
Vector of maxima. |
shape |
Vector of scaling parameters. Default value: 4. |
log, log.p |
Logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
Logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x]. |
The PERT distribution is a beta distribution extended to the domain [min, max] with mean
mu = (min + shape * mode + max)/(shape + 2)
The underlying beta distribution is specified by shape1 and shape2 defined as
shape1=(mu - min)*(2 mode-min-max)/((mode-mu)*(max - min))
shape2=shape1*(max - mu)/(mu - min)
If mu=mode, shape1 is set to 1+shape/2. David Vose proposed a modified PERT distribution with a shape parameter different from 4. The PERT distribution is frequently used to translate expert estimates of the min, max and mode of a random variable in a smooth parametric distribution.
dpert gives the density, ppert gives the distribution function, qpert gives the quantile function, and rpert generates random deviates.
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