I have a dataframe table and I would like to calculate the mahalanobis for each possible pair of column of my dataframe.
A1 A2 A3
121.4984 219.5448 250.7575
121.5195 219.5451 250.7500
121.5089 219.4667 250.5645
121.5510 219.6235 250.5645
121.8034 219.4235 250.0005
I would like to calculate the distance beetween A1 and A2, A1 and A3, A2 and A3 ... I may have up to 50 columns so If anyone has an idea how to do it :) Thanks
The function mahalanobis return the squared Mahalanobis distance, then you can do something like this:
table <- iris[1:10, -5]
coln <- combn(colnames(table), 2)
out <- apply(coln, 2, function(x) sqrt(mahalanobis(table[, x], colMeans(table[, x]), cov(table[, x]))))
colnames(out) <- apply(coln, 2, paste, collapse = "_")
out
Sepal.Length_Sepal.Width Sepal.Length_Petal.Length Sepal.Length_Petal.Width Sepal.Width_Petal.Length Sepal.Width_Petal.Width
1 0.6808740 2.1111068 1.0495913 1.2242322 1.2236349
2 3.3019215 0.4836711 0.1275204 1.0238329 1.3640406
3 0.3160289 2.0549883 0.3040872 2.1087531 0.1284711
4 0.7972596 2.3548714 0.8043597 1.3831695 0.5496880
5 1.0730825 1.1132502 0.4512262 2.1350123 2.3749610
6 3.9962218 5.6939205 6.3564033 6.0656020 5.4638846
7 3.4022539 0.8045986 2.9231608 0.6036855 1.3184087
8 0.2499919 0.2784879 0.4512262 0.2180897 0.4654446
9 2.5149505 2.8599376 2.6288828 1.8544533 2.5715289
10 1.6674153 0.2451676 2.9035422 1.3831695 2.5399376
Petal.Length_Petal.Width
1 0.2144860
2 0.2144860
3 2.2331776
4 0.5509346
5 0.2144860
6 6.9434579
7 2.3803738
8 0.5509346
9 0.2144860
10 4.4831776