Description Usage Arguments Details See Also Examples
View source: R/hclust.vector.R View source: R/hclust.vector.R
This function implements a version of the hierarchical, agglomerative clustering hclust.vector
focused on table of frequencies.
1 2 3 4 | hclustvfreq(data, freq = NULL, method = "single", metric = "euclidean",
p = NULL)
.hclustvfreq(tfq, method = "single", metric = "euclidean", p = NULL)
|
data |
any object that can be coerced into a double matrix |
freq |
a one-sided, single term formula specifying frequency weights |
method |
the agglomeration method to be used. This must be (an unambiguous abbreviation of) one of " |
metric |
the distance measure to be used. This must be one of |
p |
parameter for the Minkowski metric. |
tfq |
a frequency table |
Any variables in the formula are removed from the data set.
This function is a wrapper of hclust.vector
to be used with tables of frequencies. It use the frequency weights as parameter members
.
hclust.vector
, link{tablefreq}
1 2 3 4 5 6 7 8 9 10 |
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Attaching package: 'fastcluster'
The following object is masked from 'package:stats':
hclust
[1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 2 2 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1
[38] 1 2 1 1 1 1 2 1 1 1 1 1 2 2 2 2 2 1 1 2 2 2 2 2 2 2 2 2 2 2 2 1 1 2 2 2 2
[75] 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
[112] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3
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