Riemann (version 0.1.4)

loglkd: S3 method for mixture model : log-likelihood

Description

Given a fitted mixture model \(f(x)\) and observations \(x_1, \ldots, x_n \in \mathcal{M}\), compute the log-likelihood $$L = \log \prod_{i=1}^n f(x_i) = \sum_{i=1}^n \log f(x_i)$$.

Usage

loglkd(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

the log-likelihood.

Examples

# NOT RUN {
# ---------------------------------------------------- #
#            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
newloglkd = round(loglkd(k3, locations), 3)
print(paste0("Log-likelihood for K=3 model fit : ", newloglkd))
# }
# NOT RUN {
# }