rmf.vector: Simulate a Random Normal Vector

In pdhoff/rstiefel: Random Orthonormal Matrix Generation and Optimization on the Stiefel Manifold

Description

Simulate a random normal vector from the von Mises-Fisher distribution as described in Wood(1994).

Usage

rmf.vector(kmu)

Arguments

kmu

a vector.

Value

a vector.

Author(s)

Peter Hoff

References

Wood(1994), Hoff(2009)

Examples

## The function is currently defined as
function (kmu) 
{
    kap <- sqrt(sum(kmu^2))
    mu <- kmu/kap
    m <- length(mu)
    if (kap == 0) {
        u <- rnorm(length(kmu))
        u<-matrix(u/sqrt(sum(u^2)),m,1) 
    }
    if (kap > 0) {
        if (m == 1) {
            u <- (-1)^rbinom(1, 1, 1/(1 + exp(2 * kap * mu)))
        }
        if (m > 1) {
            W <- rW(kap, m)
            V <- rnorm(m - 1)
            V <- V/sqrt(sum(V^2))
            x <- c((1 - W^2)^0.5 * t(V), W)
            u <- cbind(NullC(mu), mu) %*% x
        }
    }
    u
  }

pdhoff/rstiefel documentation built on June 16, 2021, 5:36 p.m.