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Accommodating Outliers and Nonlinearity in Decision Models.
- Source :
- Journal of Accounting, Auditing & Finance; Spring92, Vol. 7 Issue 2, p161-190, 30p, 7 Charts
- Publication Year :
- 1992
-
Abstract
- This paper describes and compares six procedures that can be used in a regression model to adjust for outliers in the data and nonlinearities in the relationship between the dependent and independent variables. The data accommodation procedures are: (1) no-adjustment; (2) winsorizing; (3) trimming; (4) regression on ranks; (5) nonlinear regression; and (6) piecewise linear regression. The results show that the choice of data accommodation procedure has a major impact on the predictive ability and coefficient estimates of the regression model. The winsorizing and ranking procedures produce a regression model that fits the data well and has a low level of prediction error. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0148558X
- Volume :
- 7
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Journal of Accounting, Auditing & Finance
- Publication Type :
- Academic Journal
- Accession number :
- 7280258
- Full Text :
- https://doi.org/10.1177/0148558X9200700205