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Density, distribution function, quantile function and random generation for the exponential power distribution with parameters mu, sigma and k.
dexpow(x, mu = 0, sigma = 1, k = 0, log = FALSE)pexpow(q, mu = 0, sigma = 1, k = 0, lower.tail = TRUE, log.p = FALSE)qexpow(p, mu = 0, sigma = 1, k = 0, lower.tail = TRUE, log.p = FALSE)rexpow(n, mu = 0, sigma = 1, k = 0)
pexpow(q, mu = 0, sigma = 1, k = 0, lower.tail = TRUE, log.p = FALSE)
qexpow(p, mu = 0, sigma = 1, k = 0, lower.tail = TRUE, log.p = FALSE)
rexpow(n, mu = 0, sigma = 1, k = 0)
vector of quantiles.
location and scale parameters.
shape parameter.
logical; if TRUE, probabilities p are given as log(p).
logical; if TRUE (default), probabilities are \(P[X \le x ]\), otherwise, P[X > x].
vector of probabilities.
number of observations.
The Exponential distribution has density
\(f\left(x\right)=\left[\frac{e^{-\left(\frac{x-\mu}{\sigma}\right)}}{\left(1+e^{-\left(\frac{x-\mu}{\sigma}\right)}\right)^{2}}\right]\),
where \(-\infty<\mu<\infty\) is the location paramether, \(\sigma^2>0\) the scale parameter and k the shape parameter.
Lemonte A. and Baz<U+00E1>n J.L.
# NOT RUN { dexpow(1, 3, 4, 1) pexpow(1, 3, 4, 1) qexpow(0.2, 3, 4, 1) rexpow(5, 3, 4, 1) # }
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