Combining some Biased Estimation Methods with Least Trimmed Squares Regression and its Application
In the case of multicollinearity and outliers in regression analysis, the researchers are encouraged to deal with two problems simultaneously. Biased methods based on robust estimators are useful for estimating the regression coefficients for such cases. In this study we examine some robust biased e...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universidad Nacional de Colombia
|
| Series: | Revista Colombiana de Estadística |
| Subjects: | |
| Online Access: | http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-17512015000200011&lng=en&tlng=en |
| Summary: | In the case of multicollinearity and outliers in regression analysis, the researchers are encouraged to deal with two problems simultaneously. Biased methods based on robust estimators are useful for estimating the regression coefficients for such cases. In this study we examine some robust biased estimators on the datasets with outliers in x direction and outliers in both x and y direction from literature by means of the R package ltsbase . Instead of a complete data analysis, robust biased estimators are evaluated using capabilities and features of this package. |
|---|---|
| ISSN: | 0120-1751 |