BSkyPrinCompAnalysis: Principal Component Analysis

In BlueSkyStatistics/BlueSky: BlueSky Collection of Functions for Data Access, Analysis, and Formatting.

Principal Component Analysis

Description

Performs a principal components analysis on the given numeric data matrix and returns the results as an object of class princomp. Internally calls princomp in the stats package.

Usage

BSkyPrinCompAnalysis(
  vars,
  cor = FALSE,
  componentsToRetain = 0,
  generateScreeplot = FALSE,
  prefixForComponents = "",
  dataset,
  excludeEnvPrefix = FALSE
)

Arguments

vars:	The variables in a character vector to extract components from
cor:	A boolean that specifies whether the calculation should use a correlation or covariance matrix
componentsToRetain:	A numeric that Specifies the number of components to retain in the dataset. A new variable is created in the dataset for each component invoked
​generateScreeplot:	Generates a screeplot
prefixForComponents:	Prefix to use when saving the components to a dataset
dataset:	The name of the dataset as a string

Value

princomp returns a list with class "princomp" containing the following components sdev: the standard deviations of the principal components. loadings: the matrix of variable loadings (i.e., a matrix whose columns contain the eigenvectors). This is of class "loadings": see loadings for its print method. center: the means that were subtracted. scale: the scalings applied to each variable. n.obs: the number of observations. scores: if scores = TRUE, the scores of the supplied data on the principal components. These are non-null only if x was supplied, and if covmat was also supplied if it was a covariance list. For the formula method, napredict() is applied to handle the treatment of values omitted by the na.action. call: the matched call. na.action: If relevant.

BlueSkyStatistics/BlueSky documentation built on April 14, 2025, 7:39 a.m.