Description Usage Arguments Value References Examples
View source: R/ml_estimation.R
This function evaluates the log-likelihood with respect to a given threshold
parameter of a three-parametric lifetime distribution. In terms of
Maximum Likelihood Estimation this function can be optimized (optim
)
to estimate the threshold parameter.
1 2 3 4 5 6 | loglik_profiling(
x,
status,
thres,
distribution = c("weibull3", "lognormal3", "loglogistic3")
)
|
x |
A numeric vector which consists of lifetime data. Lifetime data could be every characteristic influencing the reliability of a product, e.g. operating time (days/months in service), mileage (km, miles), load cycles. |
status |
A vector of binary data (0 or 1) indicating whether unit i is a right censored observation (= 0) or a failure (= 1). |
thres |
A numeric value for the threshold parameter. |
distribution |
Supposed three-parametric distribution of the random variable. |
Returns the log-likelihood value for the data with respect to the threshold
parameter thres
.
Meeker, William Q; Escobar, Luis A., Statistical methods for reliability data, New York: Wiley series in probability and statistics, 1998
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | # Vectors:
cycles <- alloy$cycles
status <- alloy$status
# Determining the optimal loglikelihood value:
## Range of threshold parameter must be smaller than the first failure:
threshold <- seq(
0,
min(cycles[status == 1]) - 0.1,
length.out = 50
)
## loglikelihood value with respect to threshold values:
profile_logL <- loglik_profiling(
x = cycles,
status = status,
thres = threshold,
distribution = "weibull3"
)
## Threshold value (among the candidates) that maximizes the
## loglikelihood:
threshold[which.max(profile_logL)]
## plot:
plot(
threshold,
profile_logL,
type = "l"
)
abline(
v = threshold[which.max(profile_logL)],
h = max(profile_logL),
col = "red"
)
|
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