eigenPCA: Perform an Eigen Analysis to Construct Principal Components
In s-huebler/rotateS21: Shiny Data Rotation
Description
Usage
Arguments
Examples
Description
This function will allow you to construct a set of principal components using
the eigen analysis of the covariance matrix built from the input data frame. The
function will return, as a list, the covariance matrix, the linear combinations
of the principal components, the total sample variance of each component, and a
matrix containing the correlation coefficients between each linear combination and
each variable.
Usage
1
Arguments
df
, df is a data frame of quantatative variables
Examples
1
2
s-huebler/rotateS21 documentation built on Dec. 22, 2021, 8:21 p.m.
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Description Usage Arguments Examples
Description
This function will allow you to construct a set of principal components using the eigen analysis of the covariance matrix built from the input data frame. The function will return, as a list, the covariance matrix, the linear combinations of the principal components, the total sample variance of each component, and a matrix containing the correlation coefficients between each linear combination and each variable.
Usage
1 |
Arguments
df |
, df is a data frame of quantatative variables |
Examples
1 2 |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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