S3 method for mixture model : predict labels

Given a fitted mixture model of \(K\) components, predict labels of observations accordingly.

Usage

label(object, newdata)

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.

Value

a length-\(n\) vector of class labels.

Validation status

This retained legacy interface is experimental. Its full numerical and statistical contract has not been independently verified across supported inputs. See riem-method-contracts and the installed contract table for method-specific assumptions, restrictions, and evidence scope.

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)
# }