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.
diss
logical flag: if TRUE, then a data set must be specified as
data. Otherwise
a dissimilarity object must be specified as
obj.diss.
obj.diss
a dissimilarity matrix, typically the output of
daisy
or
dist. Also a vector with length n*(n-1)/2 is allowed (where n is
the number of objects), and will be interpreted in the same way as the
output of the above-mentioned functions. Missing values (NAs) are not
allowed.
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.
method
character string defining the clustering method. The three methods
implemented are "average", "complete", and "single" linkage.
save.x
logical flag: if TRUE, the standardized data is stored in the model object.
save.diss
logical flag: if TRUE, the dissimilarities are stored in the model object.
print.type
character string "None", "Short", or "Long" indicating whether to display no
printed output, the print method, or the summary method for the model.
save.name
character string giving name of data frame in which to save cluster
membership indices if
save.cluster.p=T.
save.cluster.p
logical flag indicating whether to save cluster membership indices.
save.num.groups
number of clusters to use ingenerating cluster membership indices if
save.cluster.p=T.
plot.p
logical flag indicating whether to plot the banner plot for the model.
pltree.p
logical flag indicating whether to plot the clustering tree for the model.
x
deprecated argument.
VALUE:
object of class
agnes. See
agnes.object for details.