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Dergiler / Hacettepe Journal of Mathematics and Statistics / 2012 / Cilt: 41 - Sayı: 1

Outlier detection by regression diagnostics based on robust parameter estimates

Semra TÜRKAN
Meral Candan ÇETİN
Öniz TOKTAMIŞ
Sayfa
147–155
Yayın Tarihi
2022-10-18
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

A simulation study is per- formed to compare the performance of the classical diagnostics with the proposed diagnostics based on robust M estimation to identify outliers.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:In this article, robust versions of some of the frequently used diagnos- tics are considered to identify outliers instead of the diagnostics based on the least square method.
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Temel Bulgular & Veri:These diagnostics are Cook’s distance, the Welsch-Kuh distance and the Hadi measure.
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Sonuç & Katkı:A simulation study is per- formed to compare the performance of the classical diagnostics with the proposed diagnostics based on robust M estimation to identify outliers.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Abstract

In this article, robust versions of some of the frequently used diagnos- tics are considered to identify outliers instead of the diagnostics based on the least square method. These diagnostics are Cook’s distance, the Welsch-Kuh distance and the Hadi measure. A simulation study is per- formed to compare the performance of the classical diagnostics with the proposed diagnostics based on robust M estimation to identify outliers.

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Bu Makaleye Atıf Yap

TÜRKAN, S., ÇETİN, M. C., TOKTAMIŞ, Ö. (2022). Outlier detection by regression diagnostics based on robust parameter estimates. Hacettepe Journal of Mathematics and Statistics, Cilt: 41 - Sayı: 1, 147–155. https://ajindex.com/articles/530456

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Kaynakça (17)

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