dvMF: Density function of the von Mises-Fisher distribution

In PartialNetwork: Estimating Peer Effects Using Partial Network Data

Density function of the von Mises-Fisher distribution

Description

Density function for the von Mises-Fisher distribution of dimension p with location parameter equal to mu and intensity parameter eta.

Usage

dvMF(z, theta, log.p = FALSE)

Arguments

z	is a matrix where each row is a spherical coordinate at which the density will be evaluated.
theta	is a vector of dimension p equal to \eta\mu, where \eta is the concentration parameter, and \mu the location parameter.
log.p	is logical; if TRUE, probabilities p are given as log(p).

Value

the densities computed at each point.

Examples

# Draw 1000 vectors from vMF with parameter eta = 1 and mu = c(1,0)
z <- rvMF(1000, c(1,0))

# Compute the density at z
dvMF(z, c(1,0))

# Density of c(0, 1, 0, 0) with the parameter eta = 3 and mu = c(0, 1, 0, 0)
dvMF(matrix(c(0, 1, 0, 0), nrow = 1), c(0, 3, 0, 0))

PartialNetwork documentation built on May 29, 2024, 10:08 a.m.