apd_pca {applicable}  R Documentation 
apd_pca
apd_pca()
fits a model.
apd_pca(x, ...)
## Default S3 method:
apd_pca(x, ...)
## S3 method for class 'data.frame'
apd_pca(x, threshold = 0.95, ...)
## S3 method for class 'matrix'
apd_pca(x, threshold = 0.95, ...)
## S3 method for class 'formula'
apd_pca(formula, data, threshold = 0.95, ...)
## S3 method for class 'recipe'
apd_pca(x, data, threshold = 0.95, ...)
x 
Depending on the context:

... 
Not currently used, but required for extensibility. 
threshold 
A number indicating the percentage of variance desired from the principal components. It must be a number greater than 0 and less or equal than 1. 
formula 
A formula specifying the predictor terms on the righthand side. No outcome should be specified. 
data 
When a recipe or formula is used,

The function computes the principal components that account for
up to either 95% or the provided threshold
of variability. It also
computes the percentiles of the absolute value of the principal components.
Additionally, it calculates the mean of each principal component.
A apd_pca
object.
predictors < mtcars[, 1]
# Data frame interface
mod < apd_pca(predictors)
# Formula interface
mod2 < apd_pca(mpg ~ ., mtcars)
# Recipes interface
library(recipes)
rec < recipe(mpg ~ ., mtcars)
rec < step_log(rec, disp)
mod3 < apd_pca(rec, mtcars)