qmvt {mvtnorm} | R Documentation |
Computes the equicoordinate quantile function of the multivariate t distribution for arbitrary correlation matrices based on inversion of qmvt.
qmvt(p, interval = NULL, tail = c("lower.tail", "upper.tail", "both.tails"), df = 1, delta = 0, corr = NULL, sigma = NULL, algorithm = GenzBretz(), type = c("Kshirsagar", "shifted"), ...)
p |
probability. |
interval |
optional, a vector containing the end-points of the interval to be
searched by |
tail |
specifies which quantiles should be computed.
|
delta |
the vector of noncentrality parameters of length n, for
|
df |
degree of freedom as integer. Normal quantiles are computed for |
corr |
the correlation matrix of dimension n. |
sigma |
the covariance matrix of dimension n. Either |
algorithm |
an object of class |
type |
type of the noncentral multivariate t distribution
to be computed. |
... |
additional parameters to be passed to
|
Only equicoordinate quantiles are computed, i.e., the quantiles in each
dimension coincide. Currently, the distribution function is inverted by
using the
uniroot
function which may result in limited accuracy of the
quantiles.
A list with four components: quantile
and f.quantile
give the location of the quantile and the value of the function
evaluated at that point. iter
and estim.prec
give the number
of iterations used and an approximate estimated precision from
uniroot
.
qmvt(0.95, df = 16, tail = "both")