View source: R/function_pert_estocastico.R
stochastic.pert | R Documentation |
This function calculates the average duration time for a stochastic project and the activities criticality index. It also plots the estimate density of the project duration, as well as the estimate density of the early and last times.
stochastic.pert(
prec1and2 = matrix(0),
prec3and4 = matrix(0),
distribution,
values,
percentile = 0.95,
plot.activities.times = NULL,
compilations = 1000
)
prec1and2 |
A matrix indicating the order of precedence type 1 and 2 between the activities (Default=matrix(0)). If value |
prec3and4 |
A matrix indicating the order of precedence type 3 and 4 between the activities (Default=matrix(0)). If value |
distribution |
Type of distribution that each activities' duration has. It can be NORMAL, TRIANGLE, EXPONENTIAL, UNIFORM, T-STUDENT, FDISTRIBUTION, CHI-SQUARED, GAMMA, WEIBULL, BINOMIAL, POISSON, GEOMETRIC, HYPERGEOMETRIC and EMPIRICAL. |
values |
Matrix with the parameters corresponding to the distribution associated with the duration for each activity. Considering i as an activity we have the following cases. If the distribution is TRIANGLE, then (i, 1) it is the minimum value, (i, 2) the maximum value and (i, 3) the mode. If the distribution is NORMAL, (i, 1) is the mean and (i, 2) the variance. If the distribution is EXPONENTIAL, then (i, 1) is the |
percentile |
Percentile used to calculate the maximum time allowed for the duration of the project (Default=0.95). |
plot.activities.times |
Vector of selected activities to show the distribution of their early and last times (Default=NULL). |
compilations |
Number of compilations that the function will use for average calculations (Default=1000). |
Two values, average duration time and the maximum time allowed, a critically index vector and a durations histogram.
prec1and2<-matrix(c(0,1,0,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0),nrow=5,ncol=5,byrow=TRUE)
distribution<-c("TRIANGLE","TRIANGLE","TRIANGLE","TRIANGLE","EXPONENTIAL")
values<-matrix(c(1,3,2,1/2,3/2,1,1/4,9/4,1/2,3,5,4,1/2,0,0),nrow=5,byrow=TRUE)
percentile<-0.95
plot.activities.times<-c(1,4)
stochastic.pert(prec1and2=prec1and2,distribution=distribution,values=values,
percentile=percentile,plot.activities.times=plot.activities.times)
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