mmd_boot | R Documentation |
Compute a matrix of MMD dissimilarities among bootstrapped samples of the original groups. The input data must be a “raw binary dataset”.
mmd_boot(data, angular = c("Anscombe", "Freeman"), B = 100, ...)
data |
A “raw binary dataset”, as defined in the man page
of |
angular |
Choice of a formula for angular transformation: either Anscombe or Freeman-Tukey transformation. |
B |
Numeric value: number of bootstrap samples. |
... |
Arguments for traits selection, passed to
|
This function sticks very close to Fidalgo et al's (2022) implementation. In particular, no correction for small sample sizes is applied in the MMD formula; see Fidalgo et al's (2021) for the rationale.
Note that only a “raw binary dataset” is allowed as input, since the resampling cannot be performed properly from a table of counts and frequencies.
To get a MDS plot of the dissimilarity matrix obtained with this
function, see plot.anthropmmd_boot
.
A symmetrical dissimilarity matrix of MMD values among original groups
and bootstrapped samples. This matrix is an R object of class
anthropmmd_boot
.
Frédéric Santos, frederic.santos@u-bordeaux.fr
D. Fidalgo, M. Hubbe and V. Vesolowski (2021). Population history of Brazilian south and southeast shellmound builders inferred through dental morphology. American Journal of Physical Anthropology 176(2), 192-207.
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.
plot.anthropmmd_boot
## Not run:
## 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
)
## View part of MMD matrix among bootstrapped samples:
dim(resboot)
print(resboot[1:15, 1:15])
## End(Not run)
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