Mean and standard deviation parameterised Weibull sampling function

Mean and standard deviation parameterised Weibull sampling function

rweibull_with_mean_sd(n, mean, sd)

Arguments

n	Numeric, the number of samples to take.
mean	Numeric, the mean of the distribution.
sd	Numeric the standard deviation of the distribution.

Value

A vector of samples from the Weibull distribution

Examples

## Example 
sample <- rweibull_with_mean_sd(1000, 3, 5)

mean(sample)
#> [1] 2.922596

sd(sample)
#> [1] 4.976698


hist(sample)
## Code 
rweibull_with_mean_sd
#> function (n, mean, sd) 
#> {
#>     mu <- mean
#>     sigma <- sd
#>     loc <- 0
#>     cv <- sigma/(mu - loc)
#>     if (cv < 1e-06) {
#>         nu <- cv/(sqrt(trigamma(1)) - cv * digamma(1))
#>         shape <- 1/nu
#>         scale <- (mu - loc)/(1 + nu * digamma(1))
#>     }
#>     else {
#>         aa <- log(cv^2 + 1)
#>         nu <- 2 * cv/(1 + cv)
#>         repeat {
#>             gb <- (lgamma(1 + 2 * nu) - 2 * lgamma(1 + nu) - 
#>                 aa)/(2 * (digamma(1 + 2 * nu) - digamma(1 + nu)))
#>             nu <- nu - gb
#>             if (abs(gb) < 1e-12) 
#>                 break
#>         }
#>         shape <- 1/nu
#>         scale <- exp(log(mu - loc) - lgamma(1 + nu))
#>     }
#>     stats::rweibull(n, shape = shape, scale = scale)
#> }
#> <bytecode: 0x7ff8fcf626f8>
#> <environment: namespace:NCoVUtils>