The performance of clustering approach with robust mm-estimator for multiple outlier detection in linear regression
Identifying outlier is a fundamental step in the regression model building process. Outlying observations should be identified because of their potential effect on the fitted model. As a result of the need to identify outliers, numerous outlying measures such as residuals and hat matrix diagonal are...
Main Authors: | Mohd. Azmi, Nurulhuda Firdaus, Midi, Habshah, Ismail, Noranita Fairus |
---|---|
Format: | Article |
Language: | English |
Published: |
Penerbit UTM Press
2006
|
Subjects: | |
Online Access: | http://eprints.utm.my/7941/1/JTDIS45C%5BB%5DNHuda_Firdaus.pdf |
Similar Items
-
Identifying multiple outliers in linear regression by clustering methodology using MM estimator /
by: Nurulhuda Firdaus Mohd. Azmi
Published: (2001) -
Enhanced Robust Univariate Classification Methods for Solving Outliers and Overfitting Problems
by: Okwonu, Friday Zinzendoff, et al.
Published: (2023) -
Identifying multiple outliers in linear regression using robust fit, clustering and inter-outer fences
by: Adnan, Robiah
Published: (2001) -
Robust statistical normality transformation method with outlier consideration in bitcoin exchange rate analysis
by: Abu Bakar, Nashirah, et al.
Published: (2017) -
Genetic programing and non-linear multiple regression techniques to predict backbreak in blasting operation
by: Shirani Faradonbeh, R., et al.
Published: (2016)