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This function plots a 2D MDS to represent the MMD dissimilarities
among the groups compared, after a bootstrap resampling performed with
mmd_boot.
# S3 method for anthropmmd_boot
plot(x, method = c("classical", "interval", "ratio", "ordinal"),
level = 0.95, pch = 16, gof = FALSE, xlab = NA, ylab = NA,
main = "MDS plot of original and bootstrapped samples", ...)This function returns no value by itself, and only plots a MDS in a new device.
An object of class anthropmmd_boot, produced by the
function mmd_boot.
.
Algorithm used for MDS computation; see plot.anthropmmd_result.
Numeric value between 0 and 1, confidence level for the contour lines displayed after the kernel density estimate.
Passed to plot.
Boolean; whether to display goodness of fit statistic on the plot.
Passed to plot.
Passed to plot.
Passed to plot.
Other arguments possibly passed to plot.
Frédéric Santos, frederic.santos@u-bordeaux.fr
In the current implementation, to stick to Fidalgo et al.'s (2022)
protocol, this function does not provide as much freedom as
plot.anthropmmd_result as concenrs MDS parameters and
other analysis options.
D. Fidalgo, V. Vesolowski and M. Hubbe (2022). Biological affinities of Brazilian pre-colonial coastal communities explored through boostrapped biodistances of dental non-metric traits. Journal of Archaeological Science 138, 105545.
start_mmd, stats::cmdscale
if (FALSE) {
## Load and visualize a raw binary dataset:
data(toyMMD)
head(toyMMD)
## Compute MMD among bootstrapped samples:
resboot <- mmd_boot(
data = toyMMD,
B = 50, # number of bootstrap samples
angular = "Anscombe",
strategy = "excludeQNPT", # strategy for trait selection
k = 10 # minimal number of observations required per trait
)
## MDS plot for bootstrapped samples:
plot(
x = resboot,
method = "interval", # algorithm used for MDS computation
level = 0.95 # confidence level for the contour lines
)
}
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