Description Usage Arguments Details Value Author(s) References Examples

The leverages of PCA model indicate how much influence each observation has on the PCA model. Observations with high leverage has caused the principal components to rotate towards them. It can be used to extract both "unimportant" observations as well as picking potential outliers.

1 2 | ```
## S4 method for signature 'pcaRes'
leverage(object)
``` |

`object` |
a |

Defined as *Tr(T(T'T)^(-1)T')*

The observation leverages as a numeric vector

Henning Redestig

Introduction to Multi- and Megavariate Data Analysis using Projection Methods (PCA and PLS), L. Eriksson, E. Johansson, N. Kettaneh-Wold and S. Wold, Umetrics 1999, p. 466

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pcaMethods documentation built on May 31, 2017, 3:19 p.m.

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