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Models where the least trimmed squares and least median of squares estimators are maximum likelihood

Berenguer-Rico, Vanessa; Johansen, Søren; Nielsen, Bent - 2019

Persistent link: https://www.econbiz.de/10012101101

Outlier detection algorithms for least squares time series regression

Johansen, Søren; Nielsen, Bent - 2014

Persistent link: https://www.econbiz.de/10010416823

Outlier detection algorithms for least squares time series regression

Johansen, Søren; Nielsen, Bent - 2014

Persistent link: https://www.econbiz.de/10010418994

Outlier detection algorithms for least squares time series regression

Johansen, Søren; Nielsen, Bent - 2014

Persistent link: https://www.econbiz.de/10010405202

Models Where the Least Trimmed Squares and Least Median of Squares Estimators Are Maximum Likelihood

Berenguer-Rico, Vanessa - 2019

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...

Persistent link: https://www.econbiz.de/10012862689

Models where the Least Trimmed Squares and Least Median of Squares estimators are maximum likelihood

Berenguer-Rico, Vanessa; Johansen, Søren; Nielsen, Bent - 2019

Persistent link: https://www.econbiz.de/10012316436

Models where the Least Trimmed Squares and Least Median of Squares estimators are maximum likelihood

Berenguer-Rico, Vanessa; Johansen, Søren; Nielsen, Bent - 2019

Persistent link: https://www.econbiz.de/10012492559

Models where the least trimmed squares and least median of squares estimators are maximum likelihood

Berenguer-Rico, Vanessa; Johansen, Søren; Nielsen, Bent - 2019

Persistent link: https://www.econbiz.de/10012193987