This function predicts the quantiles of a parametric lifetime distribution using the (log-)location-scale parameterization.

predict_quantile(
  p,
  dist_params,
  distribution = c("weibull", "lognormal", "loglogistic", "sev", "normal", "logistic",
    "weibull3", "lognormal3", "loglogistic3", "exponential", "exponential2")
)

Arguments

p

A numeric vector of probabilities.

dist_params

A vector of parameters. An overview of the distribution-specific parameters can be found in section 'Distributions'.

distribution

Supposed distribution of the random variable.

Value

A vector with predicted quantiles.

Details

For a given set of parameters and specified probabilities the quantiles of the chosen model are determined.

Distributions

The following table summarizes the available distributions and their parameters

  • location parameter \(\mu\),

  • scale parameter \(\sigma\) or \(\theta\) and

  • threshold parameter \(\gamma\).

The order within dist_params is given in the table header.

distributiondist_params[1]dist_params[2]dist_params[3]
"sev"\(\mu\)\(\sigma\)-
"weibull"\(\mu\)\(\sigma\)-
"weibull3"\(\mu\)\(\sigma\)\(\gamma\)
"normal"\(\mu\)\(\sigma\)-
"lognormal"\(\mu\)\(\sigma\)-
"lognormal3"\(\mu\)\(\sigma\)\(\gamma\)
"logistic"\(\mu\)\(\sigma\)-
"loglogistic"\(\mu\)\(\sigma\)-
"loglogistic3"\(\mu\)\(\sigma\)\(\gamma\)
"exponential"\(\theta\)--
"exponential2"\(\theta\)\(\gamma\)-

Examples

# Example 1 - Predicted quantiles for a two-parameter weibull distribution:
quants_weib2 <- predict_quantile(
  p = c(0.01, 0.1, 0.5),
  dist_params = c(5, 0.5),
  distribution = "weibull"
)

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