dsn(x, xi=0, omega=1, alpha=0, tau=0, dp=NULL, log=FALSE)
psn(x, xi=0, omega=1, alpha=0, tau=0, dp=NULL, engine, ...)
qsn(p, xi=0, omega=1, alpha=0, tau=0, dp=NULL, tol=1e-8, ...)
rsn(n=1, xi=0, omega=1, alpha=0, tau=0, dp=NULL)NA's) and Inf's
are allowed.NAs) are allowed+/- Inf is allowed.
With psn and qsn, it must be of length 1 if
engine="T.Owen".tau=0 (default) corresponds to
a SN distribution.dp
is specified, the individual parameters cannot be set.qsn, measured on the probability scale.dsn (default FALSE).
When TRUE, the logarithm of the density values is returned."T.Owen" or "biv.nt.prob", the latter from
package mnormt. If tau != 0 or length(alpha)>1,
"biv.nt.proT.Owendsn), probability (psn), quantile (qsn)
or random sample (rsn) from the skew-normal distribution with given
xi, omega and alpha parameters or from the extended
skew-normal if tau!=0psn and qsn make use of function T.Owen
or biv.nt.probalpha parameter which regulates
asymmetry; when alpha=0, the skew-normal distribution reduces to
the normal one. The density function of the SN distribution
in the xi=0 and omega=1 is
2*dnorm(x)*pnorm(alpha*x).
An early discussion of the skew-normal distribution is given by
Azzalini (1985); see Section 3.3 for the ESN variant,
up to a slight difference in the parameterization.
An updated extensive account is provided by Chapter 2 of Azzalini and
Capitanio (2014); the ESN variant is presented Section 2.2.
A multivariate version of the distribution is examined in Chapter 5.Azzalini, A. with the collaboration of Capitanio, A. (2014). The Skew-Normal and Related Families. Cambridge University Press, IMS Monographs series.
psn:
T.Owen, biv.nt.prob
Related distributions: dmsn, dst,
dmstpdf <- dsn(seq(-3, 3, by=0.1), alpha=3)
cdf <- psn(seq(-3, 3, by=0.1), alpha=3)
q <- qsn(seq(0.1, 0.9, by=0.1), alpha=-2)
r <- rsn(100, 5, 2, 5)Run the code above in your browser using DataLab