A coordinate‐free approach for comparing biological shapes using landmark data
if (!require("remotes")) install.packages("remotes")
remotes::install_github("psolymos/EDMAinR")
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library(EDMAinR)
#> EDMAinR 0.1-3 2020-06-12
file1 <- system.file("extdata/crouzon/Crouzon_P0_Global_MUT.xyz",
package="EDMAinR")
x1 <- read_xyz(file1)
x1
#> EDMA data: Crouzon P0 MUT
#> 3 dimensions, 47 landmarks, 28 specimens
file2 <- system.file("extdata/crouzon/Crouzon_P0_Global_NON-MUT.xyz",
package="EDMAinR")
x2 <- read_xyz(file2)
x2
#> EDMA data: Crouzon P0 UNAFF
#> 3 dimensions, 47 landmarks, 31 specimens
B <- 9
fit <- edma_fit(x1, B=B)
fit
#> EDMA nonparametric fit: Crouzon P0 MUT
#> Call: edma_fit(x = x1, B = B)
#> 3 dimensions, 47 landmarks, 28 replicates, 9 bootstrap runs
Lele, S. R., 1991. Some comments on coordinate-free and scale-invariant methods in morphometrics. American Journal of Physical Anthropology 85:407–417. doi:10.1002/ajpa.1330850405
Lele, S. R., and Richtsmeier, J. T., 1991. Euclidean distance matrix analysis: A coordinate-free approach for comparing biological shapes using landmark data. American Journal of Physical Anthropology 86(3):415–27. doi:10.1002/ajpa.1330860307
Lele, S. R., and Richtsmeier, J. T., 1992. On comparing biological shapes: detection of influential landmarks. American Journal of Physical Anthropology 87:49–65. doi:10.1002/ajpa.1330870106
Lele, S. R., and Richtsmeier, J. T., 1995. Euclidean distance matrix analysis: confidence intervals for form and growth differences. American Journal of Physical Anthropology 98:73–86. doi:10.1002/ajpa.1330980107
Hu, L., 2007. Euclidean Distance Matrix Analysis of Landmarks Data: Estimation of Variance. Thesis, Master of Science in Statistics, Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, Canada. Pp. 49.