21.1 Von Mises distribution
21.1.1 Probability density function
If \(\mu \in \mathbb{R}\) and \(\kappa \in \mathbb{R}^+\), then for \(y \in \mathbb{R}\), \[ \text{VonMises}(y|\mu,\kappa) = \frac{\exp(\kappa\cos(y-\mu))}{2\pi I_0(\kappa)} \!. \] In order for this density to properly normalize, \(y\) must be restricted to some interval \((c, c + 2\pi)\) of length \(2 \pi\), because \[ \int_{c}^{c + 2\pi} \text{VonMises}(y|\mu,\kappa) dy = 1. \] Similarly, if \(\mu\) is a parameter, it will typically be restricted to the same range as \(y\).
If \(\kappa > 0\), a von Mises distribution with its \(2 \pi\) interval of support centered around its location \(\mu\) will have a single mode at \(\mu\); for example, restricting \(y\) to \((-\pi,\pi)\) and taking \(\mu = 0\) leads to a single local optimum at the mode \(\mu\). If the location \(\mu\) is not in the center of the support, the density is circularly translated and there will be a second local maximum at the boundary furthest from the mode. Ideally, the parameterization and support will be set up so that the bulk of the probability mass is in a continuous interval around the mean \(\mu\).
For \(\kappa = 0\), the Von Mises distribution corresponds to the circular uniform distribution with density \(1 / (2 \pi)\) (independently of the values of \(y\) or \(\mu\)).
21.1.2 Sampling statement
y ~
von_mises
(mu, kappa)
Increment target log probability density with von_mises_lupdf(y | mu, kappa)
.
Available since 2.0
21.1.3 Stan functions
R
von_mises_lpdf
(reals y | reals mu, reals kappa)
The log of the von mises density of y given location mu and scale
kappa.
Available since 2.18
R
von_mises_lupdf
(reals y | reals mu, reals kappa)
The log of the von mises density of y given location mu and scale
kappa dropping constant additive terms.
Available since 2.25
R
von_mises_rng
(reals mu, reals kappa)
Generate a Von Mises variate with location mu and scale kappa (i.e.
returns values in the interval \([(\mu \mod 2\pi)-\pi,(\mu \mod 2\pi)+\pi]\)); may only be used in transformed data and generated quantities
blocks. For a description of argument and return types, see section
vectorized PRNG functions.
Available since 2.18
21.1.4 Numerical stability
Evaluating the Von Mises distribution for \(\kappa > 100\) is
numerically unstable in the current implementation. Nathanael I.
Lichti suggested the following workaround on the Stan users group,
based on the fact that as \(\kappa \rightarrow \infty\), \[
\text{VonMises}(y|\mu,\kappa) \rightarrow \text{Normal}(\mu, \sqrt{1 /
\kappa}). \] The workaround is to replace y ~ von_mises(mu,kappa)
with
if (kappa < 100) {
y ~ von_mises(mu, kappa);
} else {
y ~ normal(mu, sqrt(1 / kappa));
}