rando (version 0.2.0)

r_weibull: Generate Weibull Distributed Values

Description

Generates a set of Weibull distributed values.

Usage

r_weibull(
  shape,
  scale = 1,
  ...,
  b_scale = NULL,
  B_scale = NULL,
  n = default_n(shape, scale, b_scale, B_scale),
  .seed = NULL
)

Arguments

shape

vector of shape parameters, strictly positive

scale

vector of scale parameters, strictly positive

...

Unused

b_scale, B_scale

alternative definition of scale parameter, cannot be provided with scale, strictly positive.

n

number of observations to generate. The default_n() function will provide a default value within context

.seed

One of the following:

• NULL (default) will not change the current seed. This is the usual case for generating random numbers.

• A numeric value. This will be used to set the seed before generating the random numbers. This seed will be stored with the results.

• TRUE. A random seed value will be generated and set as the seed before the results are generated. Again, this will be stored with the results.

To extract the random seed from a previously generated set of values, use pull_seed()

Value

A numeric vector of length n

Details

This function provides alternative definitions for the scale parameter depending on the user's parametrisation of the Weibull distribution, with \(k\) = shape.

Using \(\lambda\) = scale: $$ F(x) = 1 - exp(-(x/\lambda)^k) $$

Using \(b\) = b_scale: $$ F(x) = 1 - exp(-bx^k) $$

Using \(\beta\) = B_scale: $$ F(x) = 1 - exp(-(\beta x)^k) $$

Examples

# NOT RUN {
set_n(5)

r_weibull(10)

r_weibull(1:10, 2)

r_weibull(1:10, scale = 2)
r_weibull(1:10, b_scale = 2)
r_weibull(1:10, B_scale = 2)

r_weibull(10, 2, n = 10)
# }