Influential Case Detection Methods for Factor Analysis and
Structural Equation Models
![[R logo]](../../../doc/html/Rlogo.svg)
![[Up]](../../../doc/html/left.jpg)
![[Top]](../../../doc/html/up.jpg)
Documentation for package ‘faoutlier’ version 0.7.6
Help Pages
| faoutlier | Influential case detection methods for FA and SEM |
| forward.search | Forward search algorithm for outlier detection |
| gCD | Generalized Cook's Distance |
| GOF | Goodness of Fit Distance |
| holzinger | Description of holzinger data |
| holzinger.outlier | Description of holzinger data with 1 outlier |
| LD | Likelihood Distance |
| obs.resid | Model predicted residual outliers |
| plot.forward.search | Forward search algorithm for outlier detection |
| plot.gCD | Generalized Cook's Distance |
| plot.GOF | Goodness of Fit Distance |
| plot.LD | Likelihood Distance |
| plot.obs.resid | Model predicted residual outliers |
| plot.robmah | Robust Mahalanobis |
| print.forward.search | Forward search algorithm for outlier detection |
| print.gCD | Generalized Cook's Distance |
| print.GOF | Goodness of Fit Distance |
| print.LD | Likelihood Distance |
| print.obs.resid | Model predicted residual outliers |
| print.robmah | Robust Mahalanobis |
| robustMD | Robust Mahalanobis |
| setCluster | Define a parallel cluster object to be used in internal functions |