AnthropMMD (version 4.0.3)

plot.anthropmmd_boot: Display a multidimensional scaling (MDS) plot using Fidalgo et al's (2022) bootstrap method for MMD

Description

This function plots a 2D MDS to represent the MMD dissimilarities among the groups compared, after a bootstrap resampling performed with mmd_boot.

Usage

# 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", ...)

Value

This function returns no value by itself, and only plots a MDS in a new device.

Arguments

x

An object of class anthropmmd_boot, produced by the function mmd_boot.

.

method

Algorithm used for MDS computation; see plot.anthropmmd_result.

level

Numeric value between 0 and 1, confidence level for the contour lines displayed after the kernel density estimate.

pch

Passed to plot.

gof

Boolean; whether to display goodness of fit statistic on the plot.

xlab

Passed to plot.

ylab

Passed to plot.

main

Passed to plot.

...

Other arguments possibly passed to plot.

Author

Frédéric Santos,

Details

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.

References

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.

See Also

start_mmd, stats::cmdscale

Examples

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
)
}