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Apply varimax rotation to PCA scores

Source: R/PCA.R
rotate_varimax.Rd

StackExchange reference

Usage

rotate_varimax(obj_prcomp, ncomp = 2, normalize = TRUE, savename = NULL)

Arguments

obj_prcomp

prcomp object

ncomp

integer; number of components to perform rotation with

normalize

logical; T for Kaiser normalization: rows scaled to unit length before rotation, then scaled back afterwards

savename

string; filepath (no ext.) to save results under

Value

varimax object with varimax rotation mtx rotation, varimax rotated loadings, standardized scores std_scores, and scores scores

See also

stats::varimax()

Examples

data(iris)
iris$Sample = rownames(iris)
PCA_iris <- Rubrary::run_PCA(t(iris[,c(1:4)]))
#> ** Cumulative var. exp. >= 80% at PC 1 (92.5%)

PCA_iris_varimax <- Rubrary::rotate_varimax(PCA_iris)
head(PCA_iris_varimax$scores)
#>   Scores        V1          V2
#> 1      1 -2.049927 -0.79834207
#> 2      2 -2.682972 -0.04875324
#> 3      3 -2.802785 -0.11781979
#> 4      4 -2.883760  0.16196544
#> 5      5 -2.081479 -0.81471667
#> 6      6 -1.168493 -1.39132459
head(PCA_iris_varimax$loadings)
#>       Loadings          V1          V2
#> 1 Sepal.Length  0.80645291 -0.08037849
#> 2  Sepal.Width -0.05531986 -0.39562981
#> 3 Petal.Length  1.65078788  0.62067282
#> 4  Petal.Width  0.68996837  0.26097986
Rubrary::plot_PCA(
  df_pca = PCA_iris_varimax$scores,
  PCx = "V1", PCy = "V2",
  type = "Scores",
  anno = iris[,c("Sample", "Species")],
  annoname = "Sample", annotype = "Species",
  title = "Iris PCA Varimax"
)