Analysis and Comparison of Six Robust Regression Techniques

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Atıf İçin Kopyala

Navruz G., Özdemir A. F.

Journal of Selçuk University Natural and Applied Science, cilt.3, sa.ISDS Symposium (2014), ss.46-56, 2014 (Hakemli Dergi)

• Yayın Türü: Makale / Tam Makale
• Cilt numarası: 3 Sayı: ISDS Symposium (2014)
• Basım Tarihi: 2014
• Dergi Adı: Journal of Selçuk University Natural and Applied Science
• Sayfa Sayıları: ss.46-56
• Dokuz Eylül Üniversitesi Adresli: Evet

Özet

The ordinary least squares regression can be misleading when there are outliers, heteroscedasticity and non-normality. Problems with ordinary least squares are briefly explained and six robust regression techniques, Theil-Sen, least median of squares, least trimmed squares, least absolute value, least trimmed absolute value and M-regression, that are not affected by these common problems are investigated and compared in terms of actual significance level and relative efficiency over ordinary least squares. Results are discussed and some recommendations are given.