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Communications in Statistics - Simulation and Computation Volume 47, 2018 - Issue 7
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Articles

Robust mixture regression modeling using the least trimmed squares (LTS)-estimation method

Fatma Zehra DoğruDepartment of Econometrics, Faculty of Economics and Administrative Sciences, Giresun University, Giresun, TurkeyCorrespondence[email protected]
ORCID Iconhttp://orcid.org/0000-0001-8220-2375
ORCID Icon &
Olcay ArslanDepartment of Statistics, Faculty of Science, Ankara University, Ankara, TurkeyORCID Iconhttp://orcid.org/0000-0002-7067-4997
ORCID Icon
Pages 2184-2196 | Received 10 Oct 2016, Accepted 05 Jun 2017, Published online: 18 Jul 2017

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Read on this site (2)

Fatma Zehra Doğru & Olcay Arslan. (2023) Mixture regression modelling based on the shape mixtures of skew Laplace normal distribution. Journal of Statistical Computation and Simulation 93:18, pages 3403-3420.
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Fatma Zehra Doğru, Keming Yu & Olcay Arslan. (2019) Heteroscedastic and heavy-tailed regression with mixtures of skew Laplace normal distributions. Journal of Statistical Computation and Simulation 89:17, pages 3213-3240.
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Articles from other publishers (3)

Sangkon Oh & Byungtae Seo. (2023) Semiparametric mixture of linear regressions with nonparametric Gaussian scale mixture errors. Advances in Data Analysis and Classification.
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Wennan Chang, Pengdao Dang, Changlin Wan, Xiaoyu Lu, Yue Fang, Tong Zhao, Yong Zang, Bo Li, Chi Zhang & Sha Cao. (2021) Spatially and Robustly Hybrid Mixture Regression Model for Inference of Spatial Dependence. Spatially and Robustly Hybrid Mixture Regression Model for Inference of Spatial Dependence.
Chun Yu, Weixin Yao & Guangren Yang. (2019) A Selective Overview and Comparison of Robust Mixture Regression Estimators. International Statistical Review 88:1, pages 176-202.
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