data.frame or data.sheet containing the data to cluster. Each row
corresponds to an observation, and each column corresponds to a
variable. All variables must be numeric. Missing values (NAs) are
allowed.
OPTIONAL ARGUMENTS:
variables
variables to cluster. All variables must be numeric.
subset
subsetting expression for rows.
AG na.rm
logical value indicating whether to omit rows with missing values.
metric
character string specifying the metric to be used for calculating
dissimilarities between objects. The currently available options are
"euclidean" and "manhattan". Euclidean distances are root
sum-of-squares of differences, and manhattan distances are the sum of
absolute differences. If
x is already a dissimilarity matrix, then
this argument will be ignored.
stand
logical flag: if TRUE, then the measurements in
x are standardized
before calculating the dissimilarities. Measurements are standardized
for each variable (column), by subtracting the variable's mean value
and dividing by the variables mean absolute deviation. If
x is
already a dissimilarity matrix, then this argument will be ignored.
ordratio.list
list of character strings giving column names of ratio scaled variables to be
treated as ordinal variables.
logratio.list
list of character strings giving column names of ratio scaled variables that
must be logarithmically transformed.
asymm.list
list of character strings giving column names of asymmetric binary variables.
x
deprecated argument.
VALUE:
Invisibly returns an object of class
daisy. See
dissimilarity.object for details.