qmvnorm {mvtnorm} | R Documentation |
Computes the equicoordinate quantile function of the multivariate normal
distribution for arbitrary correlation matrices
based on inversion of pmvnorm
.
qmvnorm(p, interval = NULL, tail = c("lower.tail", "upper.tail", "both.tails"), mean = 0, corr = NULL, sigma = NULL, algorithm = GenzBretz(), ...)
p |
probability. |
interval |
optional, a vector containing the end-points of the interval to be searched. This argument is IGNORED since 1.0-3. |
tail |
specifies which quantiles should be computed.
|
mean |
the mean vector of length n. |
corr |
the correlation matrix of dimension n. |
sigma |
the covariance matrix of dimension n. Either |
algorithm |
an object of class |
... |
additional parameters to be passed to
|
Only equicoordinate quantiles are computed, i.e., the quantiles in each
dimension coincide. As of version 1.0-3, the distribution function is inverted by
minimising the squared difference of the distribution function and p
. The result
is seed dependend.
A list with two components: quantile
and f.quantile
give the location of the quantile and the difference between the distribution
function evaluated at the quantile and p
.
qmvnorm(0.95, sigma = diag(2), tail = "both")