Description Usage Arguments Value References See Also Examples

Iteratively collapses the rows of a table (typically a contingency table) by selecting the pair of rows each time whose combination creates the smalled loss of chi-squared.

1 | ```
greenclust(x, correct = FALSE, verbose = FALSE)
``` |

`x` |
a numeric matrix or data frame |

`correct` |
a logical indicating whether to apply a continuity correction if and when the clustered table reaches a 2x2 dimension. |

`verbose` |
if TRUE, prints the clustered table along with r-squared and p-value at each step |

An object of class `greenclust`

which is compatible with most
`hclust`

object functions, such as `plot()`

and
`rect.hclust()`

. The height vector represents the proportion
of chi-squared, relative to the original table, seen at each clustering
step. The greenclust object also includes a vector for the chi-squared
test p-value at each step and a boolean vector indicating whether the
step had a tie for "winner".

Greenacre, M.J. (1988) "Clustering the Rows and Columns of
a Contingency Table," *Journal of Classification 5*, 39-51.
https://doi.org/10.1007/BF01901670

`greencut`

, `greenplot`

,
`assign.cluster`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
# Combine Titanic passenger attributes into a single category
tab <- t(as.data.frame(apply(Titanic, 4:1, FUN=sum)))
# Remove rows with all zeros
tab <- tab[apply(tab, 1, sum) > 0, ]
# Perform clustering on contingency table
grc <- greenclust(tab)
# Plot r-squared and p-values for each potential cut point
greenplot(grc)
# Get clusters at suggested cut point
clusters <- greencut(grc)
# Plot dendrogram with clusters marked
plot(grc)
rect.hclust(grc, max(clusters))
``` |

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