mahala: Mahalanobis Distance In metan: Multi Environment Trials Analysis

Description

Compute the Mahalanobis distance of all pairwise rows in .means. The result is a symmetric matrix containing the distances that may be used for hierarchical clustering.

Usage

 1 mahala(.means, covar, inverted = FALSE) 

Arguments

 .means A matrix of data with, say, p columns. covar The covariance matrix. inverted Logical argument. If TRUE, covar is supposed to contain the inverse of the covariance matrix.

Value

A symmetric matrix with the Mahalanobis' distance.

Author(s)

Tiago Olivoto tiagoolivoto@gmail.com

Examples

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 library(metan) library(dplyr) # Compute the mean for genotypes means <- means_by(data_ge, GEN) %>% column_to_rownames("GEN") # Compute the covariance matrix covmat <- cov(means) # Compute the distance dist <- mahala(means, covmat) # Dendrogram dend <- dist %>% as.dist() %>% hclust() %>% as.dendrogram() plot(dend) 

metan documentation built on Nov. 10, 2021, 9:11 a.m.