rbmf.vector.gibbs {rstiefel} | R Documentation |
Gibbs Sampling for the Vector-variate Bingham-von Mises-Fisher Distribution
Description
Simulate a random normal vector from the Bingham-von Mises-Fisher distribution using Gibbs sampling.
Usage
rbmf.vector.gibbs(A, c, x)
Arguments
A |
a symmetric matrix. |
c |
a vector with the same length as |
x |
the current value of the random normal vector. |
Value
a new value of the vector x
obtained by Gibbs sampling.
Note
This provides one Gibbs scan. The function should be used iteratively.
Author(s)
Peter Hoff
References
Hoff(2009)
Examples
## The function is currently defined as
function (A, c, x)
{
evdA <- eigen(A)
E <- evdA$vec
l <- evdA$val
y <- t(E) %*% x
d <- t(E) %*% c
x <- E %*% ry_bmf(y, l, d)
x/sqrt(sum(x^2))
}
[Package rstiefel version 1.0.1 Index]