Identifying outliers with sequential fences

Computational Statistics and Data Analysis

Volumn 51, Issue 8, 2007, Pages 3800-3810

  Schwertman, Neil C ^a   de Silva, Rapti ^a  

^a CALIFORNIA STATE UNIVERSITY   (United States)

Author keywords

Box plot; Box plot rule; Contaminated data; Extreme studentized deviation; Masking; Poisson; Simultaneous outlier identification; Swamping

Indexed keywords

GRAPH THEORY; POISSON DISTRIBUTION; PROBABILITY; SENSITIVITY ANALYSIS;

BOX PLOT RULE; BOX PLOTS; CONTAMINATED DATA; EXTREME STUDENTIZED DEVIATION; SIMULTANEOUS OUTLIER IDENTIFICATION; SWAMPING;

DATA REDUCTION;

EID: 33947692768     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2006.01.019     Document Type: Article

References (31)

1. Andrews D.F. A robust method for multiple linear regression. Technometrics 16 (1974) 523-531
2. Andrews D.F., and Pregibon D. Finding the outliers that matter. J. Roy. Statist. Soc. Ser. B 44 (1978) 1-36
3. Atkinson A.C. Fast very robust methods for the detection of multiple outliers. J. Amer. Statist. Assoc. 89 (1994) 1329-1339
4. Atkinson A.C., and Riani M. Robust Diagnostic Regression Analysis (2000), Springer, New York
5. Bacon-Shone J., and Fung W.K. A new graphical method for detecting single and multiple outliers in univariate and multivariate data. Appl. Statist. 36 (1987) 153-162
6. Barnett V. The study of outliers: purpose and model. Appl. Statist. 27 (1978) 242-250
7. Barnett V. Comment (on Davies and Gather (1993)). J. Amer. Statist. Assoc. 88 (1993) 795-796
8. Barnett V., and Lewis T. Outliers in Statistical Data. third ed (1995), Wiley, Chicester, England
9. Beckman R.J., and Cook R.D. Outliers... ...s. Technometrics 25 (1983) 119-163
10. Bhandary M. Detection of the numbers of outliers present in a dataset using an information theoretic criterion. Comm. Statist. Theory Methods 21 (1992) 3263-3274
11. Brant R. Comparing classical and resistant outlier rules. J. Amer. Statist. Assoc. 85 (1990) 1083-1090
12. Carling K. Resistant outlier rules and the non-Gaussian case. Comput. Statist. Data Anal. 33 3 (2000) 249-258
13. Davies L., and Gather U. The identification of multiple outliers. J. Amer. Statist. Assoc. 88 (1993) 782-792
14. Draper N.R., and Smith H. Applied Regression Analysis (1966), Wiley, New York
15. Frigge M., Hoaglin D.C., and Iglewicz B. Some implementations of the boxplot. Amer. Statist. 43 (1989) 50-54
16. Fung W.K. Unmasking outliers and leverage points: a confirmation. J. Amer. Statist. Assoc. 88 (1993) 515-519
17. Gather U., and Becker C. Outlier identification and robust methods. In: Maddala G.S., and Rao C.R. (Eds). Handbook of Statistics vol. 15 (1997) 123-143
18. Gnanadesikan R., and Kettenring J.R. Robust estimates, residuals, and outlier detection with multiresponse data. Biometrics 28 (1972) 81-124
19. Hadi A.S. Identify multiple outliers in multivariate data. J. Roy. Statist. Soc. Ser. B 54 (1992) 761-771
20. Hampel F.R. The breakdown points of the mean combined with some rejection rules. Technometrics 27 (1985) 95-107
21. Hawkins D.M. Identification of Outliers (1980), Chapman & Hall, London
22. Hoaglin D.C., and Iglewicz B. Fine-tuning, some resistant rules for outlier labeling. J. Amer. Statist. Assoc. 82 (1987) 1147-1149
23. Hoaglin D.C., Iglewicz B., and Tukey J.W. Performance of some resistant rules for outlier labeling. J. Amer. Statist. Assoc. 81 (1986) 991-999
24. Iglewicz G., and Hoaglin D.C. How to Detect and Handle Outliers (1993), ASQC Quality Press, Milwaukee
25. Milton J.S. Statistical Methods in the Biological and Health Sciences (1999), WCB/McGraw-Hill, New York
26. Penny K.I. Appropriate critical values when testing for a single multivariate outlier by using the Mahalanobis distance. Appl. Statist. 45 (1996) 73-81
27. Rosner B. On the detection of many outliers. Technometrics 17 (1975) 221-227
28. Rosner B. Percentage points for a generalized ESD many outlier procedure. Technometrics 17 (1983) 221-227
29. Rousseeuw P.J., and Leroy A.M. Robust Regression and Outlier Detection (1987), Wiley, New York
30. Schwertman, N.C., Owens, M.A., Adnan, R., 2004. A simple more general boxplot method for identifying outliers. Comput. Statist. Data Anal., to appear.
31. Tukey J.W. Exploratory Data Analysis (1977), Addison-Wesley, Reading, MA