mcs_delay_report: Adjustment of Operating Times by Delays in Report using a...

In weibulltools: Statistical Methods for Life Data Analysis

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

Description

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

Usage

mcs_delay_report(
  date_repair,
  date_report,
  time,
  status,
  distribution = "lognormal",
  details = FALSE
)

Arguments

date_repair	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.
date_report	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.
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.

Details

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).

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.

Examples

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
)

# 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
)

weibulltools documentation built on April 5, 2023, 5:10 p.m.