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MLE of the von Mises-Fisher distribution.
vmf(x, fast = FALSE, tol = 1e-07)
A matrix with the data expressed in Euclidean coordinates, i.e. unit vectors.
A boolean variable to do a faster implementation.
The tolerance to accept that the E-M algorithm used to estimate the concentration parameter has converged.
If fast = FALSE a list including all the following. If fast = TRUE less items are returned.
The mean direction.
The concentration parameter.
The mean resultant length.
The variance of the concentration parameter.
The maximum log-likelihood value.
The mean direction and concentration of a fitted von Mises-Fisher distribution are estimated.
Mardia, K. V. and Jupp, P. E. (2000). Directional statistics. Chicester: John Wiley & Sons.
Sra, S. (2012). A short note on parameter approximation for von Mises-Fisher distributions: and a fast implementation of Is(x). Computational Statistics, 27(1): 177--190.
# NOT RUN {
m <- rnorm(3)
m <- m/sqrt(sum(m^2))
m
x <- rvmf(100, m, 7)
vmf(x)
x <- rvmf(500, m, 7)
vmf(x)
# }
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