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Three-parameter Exponentiated Weibull distribution with scale \(s\), first shape \(a\) (shape1, the Weibull shape), and second shape \(b\) (shape2, the exponentiation power). The distribution is supported on \(x > 0\) and contains the ordinary Weibull (\(b = 1\)) and Exponential (\(a = 1, b = 1\)) as special cases. L-moments are computed by tanh-sinh (double-exponential) quadrature, which is well-conditioned across the full positive parameter range. Fitting uses L-BFGS-B minimisation seeded from the ExpWeibull_InitValues lookup table with scale-free L-ratio matching and analytic scale derivation.

The probability density function is: $$f(x) = \frac{b a}{s} \left(\frac{x}{s}\right)^{a-1} \exp\left(-\left(\frac{x}{s}\right)^a\right) \left(1 - \exp\left(-\left(\frac{x}{s}\right)^a\right)\right)^{b-1}, \quad x > 0$$ where:

  • \(s\) — scale parameter (scale)

  • \(a\) — first shape parameter (shape1), the Weibull shape; a = 1 gives the exponential baseline

  • \(b\) — second shape parameter (shape2), the exponentiation power; b = 1 recovers the ordinary Weibull

Usage

pexpweibull(q, scale, shape1, shape2, log.p = FALSE)

dexpweibull(x, scale, shape1, shape2, log = FALSE)

qexpweibull(p, scale, shape1, shape2)

rexpweibull(n, scale, shape1, shape2)

Arguments

scale

scale parameter.

shape1

first shape parameter.

shape2

second shape parameter.

x, q

vector of quantiles.

log, log.p

logical; if TRUE, probabilities p are given as log(p).

p

vector of probabilities.

n

number of observations. If length(n) > 1, the length is taken as the number required.