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  5. A review of detecting outlier in a circular regression model
 
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A review of detecting outlier in a circular regression model

Journal
IOP Conference Series: Materials Science and Engineering
ISSN
17578981
Date Issued
2020-03-20
Author(s)
Ramlee, Intan Mastura
Universiti Malaysia Perlis
Safwati Ibrahim
Universiti Malaysia Perlis
Leow Wai Zhe
Universiti Malaysia Perlis
Mohd Irwan Yusoff
Universiti Malaysia Perlis
DOI
10.1088/1757-899X/767/1/012048
Abstract
Circular data is very relevant and important application technique in many fields such as physical science, medical science and others. During the last few years, writers have shown a deep interest of outlier detection in the circular regression model. In this case, authors have a tendency to study and explore in detail about the outlier detection in circular regression model. This paper aims to review the outlier detection methods in circular regression model. Here, we concentrate the attention on the methods of identifying outlier in this model. These survey of circular regression models in which many interesting properties and is good enough to detect the occurrence of outlier. Through the survey may highlight the significant of methods to detect outliers in circular regressions model and provide guideline for future work to look into the research gap.
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A review of detecting outlier in a circular regression model.pdf (55.94 KB)
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