kaplan_method {weibulltools}R Documentation

Estimation of Failure Probabilities using the Kaplan-Meier Estimator

Description

[Soft-deprecated]

kaplan_method() is no longer under active development, switching to estimate_cdf is recommended.

Usage

kaplan_method(x, status, id = NULL)

Arguments

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 a unit is a right censored observation (= 0) or a failure (= 1).

id

A vector for the identification of every unit. Default is NULL.

Details

Whereas the non-parametric Kaplan-Meier estimator is used to estimate the survival function S(t) in terms of (multiple) right censored data, the complement is an estimate of the cumulative distribution function F(t). One modification is made in contrast to the original Kaplan-Meier estimator (see 'References').

Value

A tibble containing the following columns:

References

NIST/SEMATECH e-Handbook of Statistical Methods, 8.2.1.5. Empirical model fitting - distribution free (Kaplan-Meier) approach, NIST SEMATECH, December 3, 2020

Examples

# Vectors:
obs   <- seq(10000, 100000, 10000)
state <- c(0, 1, 1, 0, 0, 0, 1, 0, 1, 0)
state_2 <- c(0, 1, 1, 0, 0, 0, 1, 0, 0, 1)
uic   <- c("3435", "1203", "958X", "XX71", "abcd", "tz46",
           "fl29", "AX23","Uy12", "kl1a")

# Example 1 - Observation with highest characteristic is an intact unit:
tbl_kap <- kaplan_method(
  x = obs,
  status = state,
  id = uic
)

# Example 2 - Observation with highest characteristic is a defective unit:
tbl_kap_2 <- kaplan_method(
  x = obs,
  status = state_2
)


[Package weibulltools version 2.1.0 Index]