R/probability_estimators.R
mr_method.Rd
mr_method()
is no longer under active development, switching to estimate_cdf
is recommended.
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.
A vector of ones indicating that every unit has failed.
A vector for the identification of every unit. Default is NULL
.
Method for the estimation of the cdf. Can be "benard"
(default)
or "invbeta"
.
A character string specifying how ties are treated,
default is "max"
.
A tibble with only failed units containing the following columns:
id
: Identification for every unit.
x
: Lifetime characteristic.
status
: Status of failed units (always 1).
rank
: Assigned ranks.
prob
: Estimated failure probabilities.
cdf_estimation_method
: Specified method for the estimation of failure
probabilities (always 'mr').
This non-parametric approach (Median Ranks) is used to estimate the failure probabilities in terms of complete data. Two methods are available to estimate the cumulative distribution function F(t):
"benard"
: Benard's approximation for Median Ranks.
"invbeta"
: Exact Median Ranks using the inverse beta distribution.
# Vectors:
obs <- seq(10000, 100000, 10000)
state <- rep(1, length(obs))
uic <- c("3435", "1203", "958X", "XX71", "abcd", "tz46",
"fl29", "AX23", "Uy12", "kl1a")
# Example 1 - Benard's approximation:
tbl_mr <- mr_method(
x = obs,
status = state,
id = uic,
method = "benard"
)
#> Warning: `mr_method()` was deprecated in weibulltools 2.0.0.
#> Please use `estimate_cdf()` instead.
# Example 2 - Inverse beta distribution:
tbl_mr_invbeta <- mr_method(
x = obs,
status = state,
method = "invbeta"
)
#> Warning: `mr_method()` was deprecated in weibulltools 2.0.0.
#> Please use `estimate_cdf()` instead.