# predict_quantile: Estimation of Quantiles for Parametric Lifetime Distributions In weibulltools: Statistical Methods for Life Data Analysis

## Description

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

## Usage

 ```1 2 3``` ```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

 ```1 2 3 4 5 6 7``` ```# 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.