dsn(x, location = 0, scale = 1, shape = 0, dp = NULL, log = FALSE)
psn(x, location = 0, scale = 1, shape = 0, dp = NULL, engine, ...)
qsn(p, location = 0, scale = 1, shape = 0, dp = NULL, tol = 1e-8, engine, ...)
rsn(n = 1, location = 0, scale = 1, shape = 0, dp = NULL)NAs) and Inf's
are allowed.NAs) are allowed.psn and qsn, it must be of length 1.dp is specified, the individual
parameters cannot be set.qsn.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 the parameter is missing, a default selection rule is applied.T.Owendsn), probability (psn),
quantile (qsn) or random sample (rsn)
from the skew-normal distribution with given location, scale
and shape parameters.psn and qsn make use either of function T.Owen
or biv.nt.probshape parameter which regulates
skewness; when shape=0, the skew-normal distribution reduces to the
normal one. The density of the SN distribution in the "normalized" case
having location=0 and scale=1 is
2*dnorm(x)*pnorm(shape*x).
A multivariate version of the distribution exists.
See the reference below for additional information.dmsn, dst, T.Owen,
biv.nt.probpdf <- dsn(seq(-3,3,by=0.1), shape=3)
cdf <- psn(seq(-3,3,by=0.1), shape=3)
qu <- qsn(seq(0.1,0.9,by=0.1), shape=-2)
rn <- rsn(100, 5, 2, 5)Run the code above in your browser using DataLab