Performance evaluation of PCA tests for multiple gross error identification

In this paper, the performance of the Principal Component Test, including both the Principal Component Nodal Test (PCNT) and Principal Component Measurement Test (PCMT), is evaluated when used for the identification of multiple gross errors. A few existing gross error identification techniques are modified to replace the nodal, global and measurement tests they use, by a principal, component test. Comparative analysis indicates that PCA tests do not significantly enhance the ability in identification features of these strategies, performing worse in some cases.