In Auburngrads/SMRD: Statistical Methods For Reliability Data

library(SMRD)
SMRD:::vinny()

berkson200.ld <- frame.to.ld(berkson200,
                             response.column = c(1,2),
                             censor.column = 3,
                             case.weight.column = 4,
                             time.units = "1/5000 Seconds")

summary(berkson200.ld)

plot(berkson200.ld)
plot(berkson200.ld, dist = "Exponential")

cdfest(berkson200.ld)

berkson200.mle.exp <- mlest(berkson200.ld, 
                            distribution = "Exponential")

berkson200.mle.exp

berkson200.mle.exp$ll.text
berkson200.mle.exp$ll.value
berkson200.mle.exp$mttf.text
berkson200.mle.exp$mttf.value
berkson200.mle.exp$mle.table
berkson200.mle.exp$vcv.matrix
berkson200.mle.exp$param.corr.matrix
berkson200.mle.exp$failure.probabilities
berkson200.mle.exp$quantiles
berkson200.mle.exp$hazard.table

mleprobplot(berkson200.ld, 
            distribution = "Exponential", 
            param.loc = "bottomright")

berkson200.mle.exp <- expon.mle(berkson200.ld)

berkson200.mle.gam <- Gamma.mle(berkson200.ld)

simple.contour(berkson200.ld, 
               distribution = 'exponential', 
               xlim = c(400,800))

compare.many.exponential.profiles(theta = 5,
                                  sample.size = 3,
                                  number.simulation = 10)

compare.many.exponential.profiles(theta =5,
                                  sample.size = 1000,
                                  number.simulation = 10)