This function provides a method to construct the NNL.
Usage
nnl(distance, K)
Arguments
distance
The distance matrix on the distinct values (a "number of unique observations" by "number of unique observations" matrix).
K
The value of k in "k-MST" or "k-NNL" to construct the similarity graph.
Value
E
The edge matrix representing the similarity graph on the distinct values with the number of edges in the similarity graph being the number of rows and 2 columns. Each row records the subject indices of the two ends of an edge in the similarity graph.
# NOT RUN {n = 50d = 10dat = matrix(rnorm(d*n),n)
sam = sample(1:n, replace = TRUE)
dat = dat[sam,]
# This data has repeated observationsdat_uni = unique(dat)
E = nnl(dist(dat_uni), 1)
# }