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Remove principal components from data

Source: R/dim-reduction.R
remove_components.Rd

Reconstruct data after removing principal components. This function will reconstruct a truncated version of the original data matrix after removing the specified principal components. The source code for this function was stolen from stack exchange

Usage

remove_components(x, components = 1, ...)

Arguments

x

data.frame or matrix of original data.

components

numeric vector of components to remove from original data. Default (1)

...

Additional arguments passed to prcomp()

Value

data.frame of values in the original units after removing components

Examples

# Remove first two components from dataset
trunc <- remove_components(USArrests, components = 1:2, scale. = TRUE, center = TRUE)

# original data
head(USArrests)
#>            Murder Assault UrbanPop Rape
#> Alabama      13.2     236       58 21.2
#> Alaska       10.0     263       48 44.5
#> Arizona       8.1     294       80 31.0
#> Arkansas      8.8     190       50 19.5
#> California    9.0     276       91 40.6
#> Colorado      7.9     204       78 38.7

# reconstructed data
head(trunc)
#>              Murder  Assault UrbanPop     Rape
#> Alabama    8.879093 171.0042 68.24625 17.99226
#> Alaska     3.558807 152.5293 53.64856 36.33858
#> Arizona    5.370958 220.7384 63.64209 20.95841
#> Arkansas   7.107685 179.4374 64.56869 21.94987
#> California 5.949990 178.4936 61.64172 25.48834
#> Colorado   6.181011 146.4461 59.61149 29.53625