gleam_stats/distributions/weibull
Functions related to continuous weibull random variables.
- Available Functions
Functions
pub fn weibull_cdf(x: Float, lambda: Float, k: Float) -> Result(
Float,
String,
)
Evaluate, at a certain point, the cumulative distribution function (cdf) of a weibull random variable with scale parameter ‘lambda’ > 0 and shape parameter ‘k’ > 0.
Example:
import gleam_stats/distributions/weibull
import gleeunit/should
pub fn example() {
let lambda: Float = 1.
let k: Float = 5.
// For illustrational purposes, evaluate the cdf at the
// point -100.0
weibull.weibull_cdf(-100.0, lambda, k) |> should.equal(Ok(0.0))
}
pub fn weibull_mean(lambda: Float, k: Float) -> Result(
Float,
String,
)
Analytically compute the mean of a continuous weibull random variable
with scale parameter ‘lambda’ > 0 and shape parameter ‘k’ > 0.
pub fn weibull_pdf(x: Float, lambda: Float, k: Float) -> Result(
Float,
String,
)
Evaluate the probability density function (pdf) of a continuous weibull random variable with scale parameter ‘lambda’ > 0 and shape parameter ‘k’ > 0.
Example:
import gleam_stats/distributions/weibull
import gleeunit/should
pub fn example() {
let lambda: Float = 1.
let k: Float = 5.
// For illustrational purposes, evaluate the pdf at the
// point -100.0
weibull.weibull_pdf(-100.0, lambda, k) |> should.equal(Ok(0.0))
}
pub fn weibull_random(stream: Iterator(Int), lambda: Float, k: Float, m: Int) -> Result(
#(List(Float), Iterator(Int)),
String,
)
Generate ‘m’ random numbers from a continuous weibull distribution with scale parameter ‘lambda’ > 0 and shape parameter ‘k’ > 0.
The random numbers are generated using the inverse transform method.
Example:
import gleam/iterator.{Iterator}
import gleam_stats/generator
import gleam_stats/distributions/weibull
pub fn example() {
let seed: Int = 5
let seq: Int = 1
let lambda: Float = 1.
let k: Float = 5.
assert Ok(out) =
generators.seed_pcg32(seed, seq)
|> weibull.weibull_random(lambda, k, 5_000)
let rands: List(Float) = pair.first(out)
let stream: Iterator(Int) = pair.second(out)
}
pub fn weibull_variance(lambda: Float, k: Float) -> Result(
Float,
String,
)
Analytically compute the variance of a continuous weibull random variable
with scale parameter ‘lambda’ > 0 and shape parameter ‘k’ > 0.