jsep | R Documentation |
To calculate density function, distribution function, quantile function, and build data from random generator function for the Jones Skew Exponential Power
djsep(x, mu = 0, sigma = 1, alpha = 2, beta = 2, log = FALSE)
pjsep(
q,
mu = 0,
sigma = 1,
alpha = 2,
beta = 2,
lower.tail = TRUE,
log.p = FALSE
)
qjsep(
p,
mu = 0,
sigma = 1,
alpha = 2,
beta = 2,
lower.tail = TRUE,
log.p = FALSE
)
rjsep(n, mu = 0, sigma = 1, alpha = 2, beta = 2)
x , q |
vector of quantiles. |
mu |
a location parameter. |
sigma |
a scale parameter. |
alpha |
a shape parameter (left tail heaviness parameter). |
beta |
a shape parameter (right tail heaviness parameter). |
log , log.p |
logical; if TRUE, probabilities p are given as log(p) The default value of this parameter is FALSE |
lower.tail |
logical;if TRUE (default), probabilities are
|
p |
vectors of probabilities. |
n |
number of observations. |
Jones Skew Exponential Power
The Jones Skew Exponential Power with parameters \mu
, \sigma
,\alpha
, and \beta
has density:
f(y | \mu, \sigma, \alpha, \beta) = \left\{
\begin{array}{ll}
\frac{c}{\sigma} \exp\left(-|z|^{\alpha}\right), & \text{if } y < \mu \\
\frac{c}{\sigma} \exp\left(-|z|^{\beta}\right), & \text{if } y \geq \mu
\end{array}
\right.
where:
z = \frac{y - \mu}{\sigma},
c = \left[ \Gamma(1 + \beta^{-1}) + \Gamma(1 + \alpha^{-1}) \right]^{-1}.
djsep
gives the density , pjsep
gives the distribution function,
qjsep
gives quantiles function, rjsep
generates random numbers.
Meischa Zahra Nur Adhelia
Rigby, R.A. and Stasinopoulos, M.D. and Heller, G.Z. and De Bastiani, F. (2019) Distributions for Modeling Location, Scale, and Shape: Using GAMLSS in R.CRC Press
djsep(4, mu=0, sigma=1, alpha=2, beta=2)
pjsep(4, mu=0, sigma=1, alpha=2, beta=2)
qjsep(0.5, mu=0, sigma=1, alpha=2, beta=2)
rjsep(4, mu=0, sigma=1, alpha=2, beta=2)
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