Given a fitted mixture model of \(K\) components, predict labels of observations accordingly.
Arguments
- object
a fitted mixture model of
riemmix
class.- newdata
data of \(n\) objects (vectors, matrices) that can be wrapped by one of
wrap.*
functions in the Riemann package.
Examples
# \donttest{
# ---------------------------------------------------- #
# FIT A MODEL & APPLY THE METHOD
# ---------------------------------------------------- #
# Load the 'city' data and wrap as 'riemobj'
data(cities)
locations = cities$cartesian
embed2 = array(0,c(60,2))
for (i in 1:60){
embed2[i,] = sphere.xyz2geo(locations[i,])
}
# Fit a model
k3 = moSN(locations, k=3)
# Evaluate
newlabel = label(k3, locations)
# }