predict_quantile: Estimation of Quantiles for Parametric Lifetime Distributions

Description Usage Arguments Value Examples

Description

This function estimates the quantiles for a given set of estimated location-scale (and threshold) parameters and specified failure probabilities.

Usage

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predict_quantile(p, loc_sc_params, distribution = c("weibull",
  "lognormal", "loglogistic", "normal", "logistic", "sev", "weibull3",
  "lognormal3", "loglogistic3"))

Arguments

p

a numeric vector which consists of failure probabilities regarding the lifetime data.

loc_sc_params

a (named) numeric vector of estimated location and scale parameters for a specified distribution. The order of elements is important. First entry needs to be the location parameter μ and the second element needs to be the scale parameter σ. If a three-parametric model is used the third element is the threshold parameter γ.

distribution

supposed distribution of the random variable. The value can be "weibull", "lognormal", "loglogistic", "normal", "logistic", "sev" (smallest extreme value), "weibull3", "lognormal3" or "loglogistic3". Other distributions have not been implemented yet.

Value

A vector containing the estimated quantiles for a given set of failure probabilities and estimated parameters.

Examples

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# Example 1: Predicted quantiles for two-parameter Weibull:
quants <- predict_quantile(p = c(0.01, 0.1, 0.5), loc_sc_params = c(5, 0.5),
                           distribution = "weibull")

# Example 2: Predicted quantiles for three-parameter Weibull:
quants_weib3 <- predict_quantile(p = c(0.01, 0.1, 0.5), loc_sc_params = c(5, 0.5, 10),
                           distribution = "weibull3")

weibulltools documentation built on May 2, 2019, 11:01 a.m.