Models where the least trimmed squares and least median of squares estimators are maximum likelihood
The Least Trimmed Squares (LTS) and Least Median of Squares (LMS) estimators are popular robust regression estimators. The idea behind the estimators is to find, for a given h, a sub-sample of h good observations among n observations and estimate the regression on that sub-sample. We find models, ba...
Asıl Yazarlar: | Berenguer-Rico, V, Johansen, S, Nielsen, B |
---|---|
Materyal Türü: | Journal article |
Dil: | English |
Baskı/Yayın Bilgisi: |
2019
|
Benzer Materyaller
-
A model where the least trimmed squares estimator is maximum likelihood
Yazar:: Berenguer-Rico, V, ve diğerleri
Baskı/Yayın Bilgisi: (2023) -
Least trimmed squares: nuisance parameter free asymptotics
Yazar:: Berenguer Rico, V, ve diğerleri
Baskı/Yayın Bilgisi: (2025) -
A comparative study on the performance of maximum likelihood, generalized least square, scale-free least square, partial least square and consistent partial least square estimators in structural equation modeling
Yazar:: Raudhah Zulkifli, ve diğerleri
Baskı/Yayın Bilgisi: (2022-01-01) -
Symmetrically trimmed least squares estimation for Tobit models
Yazar:: Powell, James
Baskı/Yayın Bilgisi: (2011) -
Large Sample Behavior of the Least Trimmed Squares Estimator
Yazar:: Yijun Zuo
Baskı/Yayın Bilgisi: (2024-11-01)