rvmmix | R Documentation |
The univariate von Mises mixtures
rvmmix(n, kappa, mu, pmix) dvmmix(x, kappa, mu, pmix, log = FALSE)
n |
number of observations. Ignored if at least one of the other parameters have length k > 1, in which case, all the parameters are recycled to length k to produce k random variates. |
kappa |
vector of component concentration (inverse-variance) parameters, |
mu |
vector of component means. |
pmix |
vector of mixing proportions. |
x |
vector of angles (in radians) where the densities are to be evaluated. |
log |
logical. Should the log density be returned instead? |
pmix
, mu
and kappa
must be of the same length, with j-th element corresponding to the j-th component of the mixture distribution.
The univariate von Mises mixture distribution with component size K = length(pmix)
has density
g(x) = p[1] * f(x; κ[1], μ[1]) + ... + p[K] * f(x; κ[K], μ[K])
where p[j], κ[j], μ[j] respectively denote the mixing proportion, concentration parameter and the mean parameter for the j-th component and f(. ; κ, μ) denotes the density function of the (univariate) von Mises distribution with mean parameter μ and concentration parameter κ.
dvmmix
computes the density and rvmmix
generates random deviates from the mixture density.
kappa <- 1:3 mu <- 0:2 pmix <- c(0.3, 0.3, 0.4) x <- 1:10 n <- 10 # mixture densities calculated at each point in x dvmmix(x, kappa, mu, pmix) # number of observations generated from the mixture distribution is n rvmmix(n, kappa, mu, pmix)
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