Dissimilarity Matrix Object

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Dissimilarity Matrix Object

Arguments

`Size`	the number of objects 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 objects of the dataset.
`NA.message`	optionally, if a dissimilarity could not be computed, because of too many missing values for some objects of the dataset.

GENERATION

daisy returns this class of objects. When provided with "observations by variables" input, also the functions pam, clara and fanny 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: