Density, distribution function, and random generation for the von Mises-Fisher distribution.
Usage
dvmf(x, mu, kappa, log = FALSE)
rvmf(n, mu, kappa)
Arguments
- x
unit vector or matrix (with each row being a unit vector) of evaluation points
- mu
unit mean vector
- kappa
non-negative numeric value for the concentration parameter of the distribution.
- log
logical; if TRUE, densities are returned on the log scale.
- n
number of random values to return.
Value
dvmf gives the density and rvm generates random deviates.
Details
This implementation of dvmf allows for automatic differentiation with RTMB. rvmf is a reparameterised import from movMF::rmovMF.
Examples
set.seed(123)
# single parameter set
mu <- rep(1, 3) / sqrt(3)
kappa <- 4
x <- rvmf(1, mu, kappa)
d <- dvmf(x, mu, kappa)
# vectorised over parameters
mu <- matrix(mu, nrow = 1)
mu <- mu[rep(1,10), ]
kappa <- rep(kappa, 10)
x <- rvmf(10, mu, kappa)
d <- dvmf(x, mu, kappa)