R: Finding the Number of Significant Principal Components

# Finding the Number of Significant Principal Components

## Documentation for package ‘PCDimension’ version 1.1.14

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

agDimCPT | Divide Steps into "Long" and "Short" to Compute Auer-Gervini Dimension
agDimension | Estimating Number of Principal Components Using the Auer-Gervini Method
agDimFunction | Divide Steps into "Long" and "Short" to Compute Auer-Gervini Dimension
agDimKmeans | Divide Steps into "Long" and "Short" to Compute Auer-Gervini Dimension
agDimKmeans3 | Divide Steps into "Long" and "Short" to Compute Auer-Gervini Dimension
agDimSpectral | Divide Steps into "Long" and "Short" to Compute Auer-Gervini Dimension
agDimTtest | Divide Steps into "Long" and "Short" to Compute Auer-Gervini Dimension
agDimTtest2 | Divide Steps into "Long" and "Short" to Compute Auer-Gervini Dimension
agDimTwiceMean | Divide Steps into "Long" and "Short" to Compute Auer-Gervini Dimension
AuerGervini | Estimating Number of Principal Components Using the Auer-Gervini Method
AuerGervini-class | Estimating Number of Principal Components Using the Auer-Gervini Method
brokenStick | The Broken Stick Method
bsDimension | The Broken Stick Method
compareAgDimMethods | Compare Methods to Divide Steps into "Long" and "Short"
makeAgCpmFun | Divide Steps into "Long" and "Short" to Compute Auer-Gervini Dimension
PCDimension | Estimating Number of Principal Components Using the Auer-Gervini Method
plot-method | Estimating Number of Principal Components Using the Auer-Gervini Method
rndLambdaF | Principal Component Statistics Based on Randomization
spca | Sample PCA Dataset
spca-data | Sample PCA Dataset
summary-method | Estimating Number of Principal Components Using the Auer-Gervini Method