R/mcs_delay.R
mcs_delay_report.Rd
mcs_delay_report()
is no longer under active development, switching to
mcs_delay is recommended.
mcs_delay_report(
date_repair,
date_report,
time,
status,
distribution = "lognormal",
details = FALSE
)
a vector of class character
or Date
, in the
format "yyyy-mm-dd", indicating the date of repair of a failed unit.
Use NA
for missing elements.
a vector of class character
or Date
, in the
format "yyyy-mm-dd", indicating the date of report of a failed unit.
Use NA
for missing elements.
A numeric vector of operating times.
A vector of binary data (0 or 1) indicating whether unit i is a right censored observation (= 0) or a failure (= 1).
Supposed distribution of the random variable. Only
"lognormal"
is implemented.
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.
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.
The delay in report describes the time between the occurrence of a damage and the registration in the warranty database. For a given date where the analysis is made there could be units which had a failure but are not registered in the database and therefore treated as censored units. To overcome this problem this function uses a Monte Carlo approach for simulating the operating times of (multiple) right censored observations, taking account of reporting delays. The simulation is based on the distribution of operating times that were calculated from complete data, i.e. failed items (see dist_delay_report).
date_of_repair <- c(NA, "2014-09-15", "2015-07-04", "2015-04-10", NA,
NA, "2015-04-24", NA, "2015-04-25", "2015-04-24",
"2015-06-12", NA, "2015-05-04", NA, NA,
"2015-05-22", NA, "2015-09-17", NA, "2015-08-15",
"2015-11-26", NA, NA)
date_of_report <- c(NA, "2014-10-09", "2015-08-28", "2015-04-15", NA,
NA, "2015-05-16", NA, "2015-05-28", "2015-05-15",
"2015-07-11", NA, "2015-08-14", NA, NA,
"2015-06-05", NA, "2015-10-17", NA, "2015-08-21",
"2015-12-02", NA, NA)
op_time <- rep(1000, length(date_of_repair))
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_report(
date_repair = date_of_repair,
date_report = date_of_report,
time = op_time,
status = status,
distribution = "lognormal",
details = FALSE
)
#> Warning: `mcs_delay_report()` was deprecated in weibulltools 2.0.0.
#> Please use `mcs_delay()` instead.
# Example 2 - Detailed list output:
list_detail <- mcs_delay_report(
date_repair = date_of_repair,
date_report = date_of_report,
time = op_time,
status = status,
distribution = "lognormal",
details = TRUE
)
#> Warning: `mcs_delay_report()` was deprecated in weibulltools 2.0.0.
#> Please use `mcs_delay()` instead.