predict_quantile: Prediction of Quantiles for Parametric Lifetime Distributions

In weibulltools: Statistical Methods for Life Data Analysis

Prediction of Quantiles for Parametric Lifetime Distributions

Description

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

Usage

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.

Details

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

Value

A vector with predicted quantiles.

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.

distribution	dist_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"
)

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