Principal component analysis (PCA) is a mathematical algorithm that reduces the dimensionality of the data while retaining most of the variation in the data set 1. It accomplishes this reduction ...

The principal components are sorted by descending order of their variances, which are equal to the associated eigenvalues. Principal components can be used to reduce the number of variables in ...

Dillon and Goldstein (1984) provide the following formal definition of principal components analysis (PCA): Principal components analysis transforms the original set of variables into a smaller set of ...

Dimensional variations at different measuring points are usually correlated with each other. The method presented in this case study is based on the use of principal component analysis (PCA) (Yang, ...