## Abstract A diagnostic procedure for detecting additive and innovation outliers as well as level shifts in a regression model with ARIMA errors is introduced. The procedure is based on a robust estimate of the model parameters and on innovation residuals computed by means of robust filtering. A M
Outlier detection by means of robust regression estimators for use in engineering science
β Scribed by Serif Hekimoglu; R. Cuneyt Erenoglu; Jan Kalina
- Book ID
- 111841389
- Publisher
- SP Zhejiang University Press
- Year
- 2009
- Tongue
- English
- Weight
- 184 KB
- Volume
- 10
- Category
- Article
- ISSN
- 1009-3095
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This work describes the use of the combination of carbon black as an antibody label, a membrane-based immunochromatographic device, and a flatbed scanner as a quantitative test system. The scanner detected 0.4 -345 ng carbon black/mm 2 on a nitrocellulose membrane (0.2-170 amol carbon black/mm 2 ) w