emCenWbMix.T2: EM algorithm for the Type-II right censored Weibull Mixture...

In extWeibQuant: Estimate Lower Extreme Quantile with the Censored Weibull MLE and Censored Weibull Mixture

Description

This is the interface for the EM algorithm of censored Weibull mixture for Type II censored data. The description of the Weibull mixture model can be found in emCenWbMix.T1.

Usage

emCenWbMix.T2(dat, n, iniParam = NULL, useC = FALSE, conCr = 1e-06, nIter = 10000)

Arguments

dat	A vector of the observations after censoring. None NA or negative values allowed.
n	The original sample size, including both the censored and uncensored observations. See cenWbMLE.T2.
iniParam	See emCenWbMix.T1
useC	See emCenWbMix.T1
conCr	See emCenWbMix.T1
nIter	See emCenWbMix.T1

Value

See emCenWbMix.T1

References

See emCenWbMix.T1

See Also

rweibull, quanWbMix, simWbMix, cenWbMLE.T2, emCenWbMix.T1

Examples

mmix = rbind(c(0.7, 5, 7),c(0.3, 15, 6))
vmix = c(mmix) #A vector version of the paramters
set.seed(1)
y <- sort(simWbMix(300, mmix)) #Generate the data
#The uncensored EM
emCenWbMix.T2(y, 300, iniParam=vmix, useC=TRUE)
#Type II censoring with the largest half of the data censored.
emCenWbMix.T2(y[1:150], 300, iniParam=vmix, useC=TRUE)

Example output

$convergence
[1] 0

$nllh
[1] 511.1865

$estimates
             Proportion     Shape    Scale
Population 1  0.7279865  4.720902 6.888439
Population 2  0.2720135 11.763734 6.115837

$iniParam
[1]  0.7  0.3  5.0 15.0  7.0  6.0

$convergence
[1] 0

$nllh
[1] 347.6727

$estimates
             Proportion     Shape    Scale
Population 1  0.8330828  4.676754 6.988447
Population 2  0.1669172 25.300135 5.836921

$iniParam
[1]  0.7  0.3  5.0 15.0  7.0  6.0

extWeibQuant documentation built on May 1, 2019, 10:31 p.m.