nested_hclust {tidypaleo} | R Documentation |
Nested (Constrained) hierarchical clustering
Description
Powered by chclust and hclust; broken stick using bstick.
Usage
nested_hclust(
.data,
data_column = "data",
qualifiers_column = "qualifiers",
distance_fun = stats::dist,
n_groups = NULL,
...,
.fun = stats::hclust,
.reserved_names = character(0)
)
nested_chclust_conslink(
.data,
data_column = "data",
qualifiers_column = "qualifiers",
distance_fun = stats::dist,
n_groups = NULL,
...
)
nested_chclust_coniss(
.data,
data_column = "data",
qualifiers_column = "qualifiers",
distance_fun = stats::dist,
n_groups = NULL,
...
)
Arguments
.data |
A data frame with a list column of data frames, possibly created using nested_data. |
data_column |
An expression that evalulates to the data object within each row of .data |
qualifiers_column |
The column that contains the qualifiers |
distance_fun |
|
n_groups |
The number of groups to use (can be a vector or expression using vars in .data) |
... |
|
.fun |
Function powering the clustering. Must return an hclust object of some kind. |
.reserved_names |
Names that should not be allowed as columns in any data frame within this object |
Value
.data
with additional columns
References
Bennett, K. (1996) Determination of the number of zones in a biostratigraphic sequence. New Phytologist, 132, 155-170. doi:10.1111/j.1469-8137.1996.tb04521.x (Broken stick)
Grimm, E.C. (1987) CONISS: A FORTRAN 77 program for stratigraphically constrained cluster analysis by the method of incremental sum of squares. Computers & Geosciences, 13, 13-35. doi:10.1016/0098-3004(87)90022-7
Juggins, S. (2017) rioja: Analysis of Quaternary Science Data, R package version (0.9-15.1). (https://cran.r-project.org/package=rioja).
See hclust for hierarchical clustering references
Examples
library(tidyr)
library(dplyr, warn.conflicts = FALSE)
nested_coniss <- keji_lakes_plottable %>%
group_by(location) %>%
nested_data(depth, taxon, rel_abund, fill = 0) %>%
nested_chclust_coniss()
# plot the dendrograms using base graphics
plot(nested_coniss, main = location, ncol = 1)
# plot broken stick dispersion to verify number of plausible groups
library(ggplot2)
nested_coniss %>%
select(location, broken_stick) %>%
unnest(broken_stick) %>%
tidyr::gather(type, value, broken_stick_dispersion, dispersion) %>%
ggplot(aes(x = n_groups, y = value, col = type)) +
geom_line() +
geom_point() +
facet_wrap(vars(location))