Name
Abstract | ||
|---|---|---|
Usually, in the regression models, the data are contaminated with unusually observations (outliers). For that reason the last 30years have developed robust regression estimators. Among them some of the most famous are Least Trimmed Squares (LTS), MM, Penalized Trimmed Square (PTS) and others. Most of these methods, especially PTS, are based on initial leverage, concerning x outlying observations, of the data sample. However, often, multiple x-outliers pull the distance towards their value, causing leverage bias, and this is the masking problem. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.simpat.2014.06.002 | Simulation Modelling Practice and Theory |
Keywords | Field | DocType |
Robust regression,Outlier detection,LTED optimization,Leverage-points,Monte-Carlo simulation | Least trimmed squares,Computer science,Regression analysis,Outlier,Partial leverage,Robust regression,Robust statistics,Leverage (statistics),Statistics,Estimator | Journal |
Volume | ISSN | Citations |
47 | 1569-190X | 0 |
PageRank | References | Authors |
0.34 | 2 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| C. Chatzinakos | 1 | 2 | 1.12 |
| G. Zioutas | 2 | 11 | 3.60 |