

   DDiissttaannccee MMaattrriixx CCoommppuuttaattiioonn

        dist(x, method = "euclidean", diag = FALSE, upper=FALSE)

        print.dist(dist.obj, diag = NULL, upper = NULL)
        as.matrix.dist(dist.obj)
        as.dist(m, diag = NULL, upper = NULL)

   AArrgguummeennttss::

          x: A matrix or (data frame).  Distances between the
             rows of `x' will be computed.

     method: The distance measure to be used. This must be one
             of `"euclidean"', `"maximum"', `"manhattan"',
             `"canberra"' or `"binary"'.  Any unambiguous sub-
             string can be given.

       diag: A logical value indicating whether the diagonal of
             the distance matrix should be printed by
             `print.dist'.

      upper: A logical value indicating whether the upper tri-
             angle of the distance matrix should be printed by
             `print.dist'.

          m: A distance matrix to be converted to a dist object
             (only lower triangle is used, the rest is
             ignored).

   DDeessccrriippttiioonn::

        This function computes and returns the distance matrix
        computed by using the specified distance measure to
        compute the distances between the rows of `x'.

   DDeettaaiillss::

        Available distance measures are (written for two vec-
        tors x and y):

           * Euclidean: Usual square distance between the two
             vectors (2 norm).

           * Maximum: Maximum distance between two components
             of x and y (supremum norm)

           * Manhattan: Absolute distance between the two vec-
             tors (1 norm).

           * Canberra: sum(|x_i - y_i| / |x_i + y_i|)

           * Count the number of different bits in x and y
             where at least one of the two bits is 1, i.e.,
             components where both bits are zero are ignored.

        The functions `as.matrix.dist()' and `as.dist()' can be
        used for conversion between objects of class `"dist"'
        and conventional distance matrices and vice versa.

   VVaalluuee::

        The lower triangle of the distance matrix stored by
        columns in a single vector.  The vector has the
        attributes `"Size"', `"Diag"', `"Upper"', `"Labels"'
        and `"class"' equal to `"dist"'.

   RReeffeerreenncceess::

        Mardia, K. V., J. T. Kent and J. M. Bibby (1979).  Mul-
        tivariate Analysis, London: Academic Press.

   SSeeee AAllssoo::

        `hclust'.

   EExxaammpplleess::

        x <- matrix(rnorm(100),nrow=5)
        dist(x)
        dist(x, diag = TRUE)
        dist(x, upper = TRUE)
        m <- as.matrix(dist(x))
        as.dist(m)

