dst(x, location = 0, scale = 1, shape = 0, df = Inf, dp = NULL, log = FALSE)
pst(x, location = 0, scale = 1, shape = 0, df = Inf, dp = NULL, ...)
qst(p, location = 0, scale = 1, shape = 0, df = Inf, tol = 1e-06, dp = NULL, ...)
rst(n = 1, location = 0, scale = 1, shape = 0, df = Inf, dp = NULL)
NA
s) are allowed.pst
and qst
,
it must be of length 1.df=Inf
which corresponds
to the skew-normal distribution.dp
is specified, the individual
parameters cannot be set.qsn
.integrate
.dst
), probability (pst
), quantiles (qst
)
and random sample (rst
) from the skew-$t$ distribution with given
location
, scale
, shape
and df
parameters.shape
parameter which regulates
skewness; when shape=0
, the skew-$t$ distribution reduces to the
usual Student's $t$ distribution. When df=Inf
, it reduces to the
skew-normal distribution. A multivariate version of the distribution exists.
See the reference below for additional information.dmst
, dsn
, psn
pdf <- dst(seq(-4,4,by=0.1), shape=3, df=5)
rnd <- rst(100, 5, 2, -5, 8)
q <- qst(c(0.25,0.5,0.75), shape=3, df=5)
pst(q, shape=3, df=5) # must give back c(0.25,0.5,0.75)
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