Arguments
Size
the number of observations in the dataset.
Metric
the metric used for calculating the dissimilarities. Possible values are
"euclidean", "manhattan", "mixed" (if variables of different types were
present in the dataset), and "unspecified".
Labels
optionally, contains the labels, if any, of the observations of the dataset.
NA.message
optionally, if a dissimilarity could not be computed, because of too many
missing values for some observations of the dataset.
GENERATION
daisy returns this class of objects.
Also the functions pam, clara, fanny, agnes, and diana return
a dissimilarity object, as one component of their return objects.METHODS
The "dissimilarity" class has methods for the following generic functions:
print.STRUCTURE
The dissimilarity matrix is symmetric, and hence is represented as a vector
to save storage space.
For i less than j, the dissimilarity between row i and row j is element
nrow(x)*(i-1) - i*(i-1)/2 + j-i of that vector.
The length of the vector is nrow(x)*(nrow(x)-1)/2,
that is, it is of order nrow(x) squared.
The object has the following attributes: