Citation
Leong Y. S., . Identifying anomalous laboratories in interlaboratory crosscheck programme by multivariate outlier analysis. pp. 54-59. ISSN 0127-7065
Abstract
Anomalous laboratories can be identified by multivariate outlier analysis involving Mahalanobis distance measure. The power in identifying an outlier is increased when higher dimensional multivariate analysis is used resulting in an improvement over Youdens two-sample diagram. On the other hand the size of the samples and the complexity of the analysis are increased. An outlier tends to tie far out from the main body of points in a graphical display of the first two principal components.
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Abstract
Anomalous laboratories can be identified by multivariate outlier analysis involving Mahalanobis distance measure. The power in identifying an outlier is increased when higher dimensional multivariate analysis is used resulting in an improvement over Youdens two-sample diagram. On the other hand the size of the samples and the complexity of the analysis are increased. An outlier tends to tie far out from the main body of points in a graphical display of the first two principal components.
Additional Metadata
| Item Type: | Article |
|---|---|
| AGROVOC Term: | Hevea rubber |
| AGROVOC Term: | Data collection |
| AGROVOC Term: | Multivariate analysis |
| AGROVOC Term: | Measurement |
| AGROVOC Term: | Laboratory experimentation |
| AGROVOC Term: | laboratory techniques |
| AGROVOC Term: | Plasticity |
| AGROVOC Term: | Analysis of variance |
| Geographical Term: | Malaysia |
| Depositing User: | Ms. Suzila Mohamad Kasim |
| Last Modified: | 28 Apr 2025 05:14 |
| URI: | http://webagris.upm.edu.my/id/eprint/23545 |
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