Outlier detection in circular regression model using minimum spanning tree method
The existence of outliers in a circular regression model can lead to many errors, for example in inferences and parameter estimations. Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. The proposed algorithms are extended from Sa...
Main Authors: | Nur Faraidah, Muhammad Di, Siti Zanariah, Satari, Roslinazairimah, Zakaria |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
Universiti Malaysia Pahang
2019
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/24692/ http://umpir.ump.edu.my/id/eprint/24692/1/29.1%20Outlier%20detection%20in%20circular%20regression%20model%20using%20minimum%20spanning%20tree%20method.pdf |
Similar Items
-
The Multiple Outliers Detection using Agglomerative Hierarchical Methods in Circular Regression Model
by: Siti Zanariah, Satari, et al.
Published: (2017) -
Single-linkage method to detect multiple outliers with different outlier scenarios in circular regression model
by: Siti Zanariah, Satari, et al.
Published: (2018) -
Detection of different outlier scenarios in circular regression model using single-linkage method
by: N. M. F., Di, et al.
Published: (2017) -
Outlier detection in a circular regression model
by: Adzhar Rambli,, et al.
Published: (2015) -
Parameter estimation and outlier detection for some types of circular model
by: Siti Zanariah, Satari
Published: (2015)