mvtnorm (version 0.9-8)

qmvt: Quantiles of the Multivariate t Distribution

Description

Computes the equicoordinate quantile function of the multivariate t distribution for arbitrary correlation matrices based on an inversion of the algorithms by Genz and Bretz.

Usage

qmvt(p, interval = c(-10, 10), tail = c("lower.tail", 
     "upper.tail", "both.tails"), df = 1, delta = 0, corr = NULL, 
     sigma = NULL, algorithm = GenzBretz(), ...)

Arguments

p

probability.

interval

a vector containing the end-points of the interval to be searched by uniroot.

tail

specifies which quantiles should be computed. lower.tail gives the quantile $x$ for which $P[X \le x] = p$, upper.tail gives $x$ with $P[X > x] = p$ and both.ta

delta

the vector of noncentrality parameters of length n.

df

degree of freedom as integer.

corr

the correlation matrix of dimension n.

sigma

the covariance matrix of dimension n. Either corr or sigma can be specified. If sigma is given, the problem is standardized. If neither corr nor sigm

algorithm

an object of class GenzBretz defining the hyper parameters of this algorithm.

...

additional parameters to be passed to uniroot.

Value

• 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.

Details

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.

See Also

pmvnorm, qmvt

Examples

qmvt(0.95, df = 16, tail = "both")