binaryClust: Cluster Matrix of Binary Censored Data

Description

Performs clustering of a matrix of 0s and 1s, ie. the censoring indicator columns for multiple variables. If there are multiple detection limits within a column first convert the 0/1 designated to be Below vs Above the highest detection limit in the column. Detection limits may differ among columns.

Usage

binaryClust(
  data,
  method = "ward.D2",
  group = NULL,
  ncluster = NULL,
  plotncluster = TRUE,
  clustIndex = "all"
)

Value

Prints a cluster dendrogram based on clustering method and outputs a list of clusters and hierarchical cluster analysis results

Arguments

data: A data frame containing only the 0/1 columns, one column per chemical parameter.
method: Method of forming clusters. The default is "ward.D2", which is appropriate for a variety of types of data. Another appropriate option is “average” – average distances between cluster centers. See the vegan package for other possible clustering methods.
group: Optional grouping variable. If used, sites being clustered will be represented by their group name, rather than by the row number.
ncluster: Optional number of clusters to be differentiated on the graph. Clusters are fenced off with rectangles.
plotncluster: default is TRUE logical flags to add identification of clusters on dendrogram
clustIndex: Optional, if not specified, potential number of clusters will be determined based on the mean best number of clusters across all indicies. For a specific index, see details

Details

If a specific index is desired to determine the best number of clusters see NbClust::NbClust for index values.

References

Helsel, D.R., 2011. Statistics for Censored Environmental Data using Minitab and R, 2nd ed. John Wiley & Sons, USA, N.J.

Examples

Run this code

data(PbHeron)

# without group specified
binaryClust(PbHeron[,4:15])

# With Group argument
binaryClust(PbHeron[,4:15],group=PbHeron$DosageGroup)

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