dist_mean_boot: Bootstrapped distance between two arrays

In fruciano/GeometricMorphometricsMix: Miscellaneous functions useful for geometric morphometrics

Bootstrapped distance between two arrays

Description

Computes bootstrapped estimates of the mean distance between two groups and their confidence intervals.

Usage

dist_mean_boot(A, B, boot = 1000, ci = 0.95, nA = nrow(A), nB = nrow(B))

Arguments

A, B	Matrices or data frames containing data (observations in rows, variables in columns).
boot	number of bootstrap resamples
ci	width of the confidence interval
nA, nB	sample sizes for each bootstrapped group (defaults to original sample size)

Details

This may be useful to compare whether the differences between two groups are larger or smaller than differences between two other groups.

For instance, if we wanted to quantify shape sexual dimorphism in two populations, we could run this analysis separately for the two populations and then check the confidence intervals. If the two confidence intervals are disjunct there is evidence for the two populations having different levels of sexual dimorphism.

The computation performs bootstrap by resampling with replacement within each of the two groups and at each round computing the Euclidean distance between the two groups. It is also possible to resample at a different sample size than the one in the data using the attributes nA and nB.

Notice that the confidence interval is expressed on a scale between 0 and 1 and not as a percentage (e.g., 0.95 means 95

Value

The function outputs a named vector with the mean, median, upper and lower confidence interval bounds obtained from the bootstrapped samples

fruciano/GeometricMorphometricsMix documentation built on Nov. 30, 2024, 3:12 a.m.