plot.bayesian.vam | R Documentation |
For bayesian.vam
object, plots the Bayesian estimations (mean and 0.95 credibility interval) of the characteristics of a virtual age model for Corrective Maintenance (CM) and planned Preventive Maintenance (PM).
plot.bayesian.vam(obj,type,from,to,length.out=101,by,system.index=1,cm.type=NA,pm.type=NA,add=FALSE,nb.proposal=500,col=c("blue","black"),lty=c(1,3),lwd=c(1,1),...)
obj |
an object of class |
type |
specifies which characteristic to plot:
By default, PM times are also represented, but "-pm" can be added at the end of the string |
from, to |
optional arguments specifying the range time over which the characteristic will be plotted. |
by |
time increment between two successive maintenance time at which the characteristic will be plotted. |
length.out |
When provided, |
system.index |
the index of the system for which to plot the characteristic. |
cm.type |
how to additionally represent the CM times or the cumulative number of CM in the "I" case. Possible types are "p" for points and "l" for lines. |
pm.type |
how to additionally represent the PM times. Possible types are "p" for points and "l" for lines. |
add |
if |
nb.proposal |
an optional argument specifying the size of the simulated sample of the posterior distribution (used to compute the estimation and credibility interval of the plotted characteristic). |
col |
a vector specifying the lines colors corresponding to the mean and the credibility interval. |
lty |
a vector specifying the lines types corresponding to the mean and the credibility interval. |
lwd |
a vector specifying the lines width corresponding to the mean and the credibility interval. |
... |
Further classical graphical parameters specifying the characteristic of the plot. Others non usual arguments can also be added in order to specify the additional representation of the CM and PM times: |
If the run.bayesian.vam
method has already been executed with arguments history=TRUE
and nb>=nb.proposal
, it is not executed again and the simulated sample of the posterior distribution memorized in obj
is used (only the nb.proposal
first simulated values are used). Otherwise the run.bayesian.vam
method is executed.
R. Drouilhet et L. Doyen
bayesian.vam
to define the Bayesian object.
run.bayesian.vam
to compute the Bayesian method.
summary.bayesian.vam
to produce a result summary of the Bayesian method.
coef.bayesian.vam
to extract the parameters estimation values of the Bayesian method.
hist.bayesian.vam
for plotting the histogram of the posterior distribution of the parameters.
simARAInf<-sim.vam( ~ (ARAInf(.4) | Weibull(.001,2.5)))
simData<-simulate(simARAInf,30)
bayesARAInf <- bayesian.vam(Time & Type ~ (ARAInf(~Unif(0,1)) | Weibull(~Unif(0,1),~Unif(2,4))),data=simData)
run(bayesARAInf,profile.alpha=TRUE,history=TRUE)
plot(bayesARAInf,'i')
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