Adjustment of Operating Times by Delays in Registration using a Monte Carlo Approach

mcs_delay_register() is no longer under active development, switching to mcs_delay is recommended.

mcs_delay_register(
  date_prod,
  date_register,
  time,
  status,
  distribution = "lognormal",
  details = FALSE
)

Arguments

date_prod: A vector of class character or Date, in the format "yyyy-mm-dd", indicating the date of production of a unit. Use NA for missing elements.
date_register: A vector of class character or Date, in the format "yyyy-mm-dd", indicating the date of registration of a unit. Use NA for missing elements.
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 "lognormal" is implemented.
details: A logical. If FALSE the output consists of a vector with corrected operating times for the censored units and the input operating times for the failed units. If TRUE the output consists of a detailed list, i.e the same vector as described before, simulated random numbers and estimated distribution parameters.

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 of x_sim is equal to the number of censored observations.
coefficients : Estimated coefficients of supposed distribution.

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).

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
)
#> Warning: `mcs_delay_register()` was deprecated in weibulltools 2.0.0.
#> Please use `mcs_delay()` instead.

# 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
)
#> Warning: `mcs_delay_register()` was deprecated in weibulltools 2.0.0.
#> Please use `mcs_delay()` instead.