mcs_delay_register {weibulltools} | R Documentation |
Adjustment of Operating Times by Delays in Registration using a Monte Carlo Approach
Description
mcs_delay_register()
is no longer under active development, switching
to mcs_delay is recommended.
Usage
mcs_delay_register(
date_prod,
date_register,
time,
status,
distribution = "lognormal",
details = FALSE
)
Arguments
date_prod |
A vector of class |
date_register |
A vector of class |
time |
A numeric vector of operating times. |
status |
A vector of binary data (0 or 1) indicating whether unit i is a right censored observation (= 0) or a failure (= 1). |
distribution |
Supposed distribution of the random variable. Only
|
details |
A logical. If |
Details
In general the amount of information about units in the field, that have not failed yet, are rare. For example it is common that a supplier, who provides parts to the automotive industry does not know when a vehicle was put in service and therefore does not know the exact operating time of the supplied parts. This function uses a Monte Carlo approach for simulating the operating times of (multiple) right censored observations, taking account of registering delays. The simulation is based on the distribution of operating times that were calculated from complete data (see dist_delay_register).
Value
A numeric vector of corrected operating times for the censored units
and the input operating times for the failed units if details = FALSE
.
If details = TRUE
the output is a list which consists of the following elements:
-
time
: Numeric vector of corrected operating times for the censored observations and input operating times for failed units. -
x_sim
: Simulated random numbers of specified distribution with estimated parameters. The length ofx_sim
is equal to the number of censored observations. -
coefficients
: Estimated coefficients of supposed distribution.
Examples
date_of_production <- c("2014-07-28", "2014-02-17", "2014-07-14",
"2014-06-26", "2014-03-10", "2014-05-14",
"2014-05-06", "2014-03-07", "2014-03-09",
"2014-04-13", "2014-05-20", "2014-07-07",
"2014-01-27", "2014-01-30", "2014-03-17",
"2014-02-09", "2014-04-14", "2014-04-20",
"2014-03-13", "2014-02-23", "2014-04-03",
"2014-01-08", "2014-01-08")
date_of_registration <- c(NA, "2014-03-29", "2014-12-06", "2014-09-09",
NA, NA, "2014-06-16", NA, "2014-05-23",
"2014-05-09", "2014-05-31", NA, "2014-04-13",
NA, NA, "2014-03-12", NA, "2014-06-02",
NA, "2014-03-21", "2014-06-19", NA, NA)
op_time <- rep(1000, length(date_of_production))
status <- c(0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0)
# Example 1 - Simplified vector output:
x_corrected <- mcs_delay_register(
date_prod = date_of_production,
date_register = date_of_registration,
time = op_time,
status = status,
distribution = "lognormal",
details = FALSE
)
# Example 2 - Detailed list output:
list_detail <- mcs_delay_register(
date_prod = date_of_production,
date_register = date_of_registration,
time = op_time,
status = status,
distribution = "lognormal",
details = TRUE
)