1
Master's student in Mathematical Statistics, Ferdowsi University of Mashhad,
2
Assistant Professor, Ferdowsi University of Mashhad
Abstract
One of the important issues in any statistical analysis is the presence of unexpected observations. Some observations are not part of the data under study and are known as outliers. Studies have shown that outliers affect the performance of standard statistical methods in models and predictions. The purpose of this article is to present a package in the R software for identifying outliers in circular-circular regression, which was written by the author of this article. First, a brief explanation of circular data and circular regression of data is given, then the packages in the R software for performing circular regression are introduced, the functions in the CircOutlier package are described, and an example is provided for each of the functions.
Ghazanfari Hissari, A. & Sarmad, M. (2016). Introducing the CircOutlier package for identifying outliers in circular-circular regression. Andishe_ye Amari, 20(2), 11-16.
MLA
Ghazanfari Hissari, A., & Sarmad, M. "Introducing the CircOutlier package for identifying outliers in circular-circular regression", Andishe_ye Amari, 20, 2, 2016, 11-16.
HARVARD
Ghazanfari Hissari A., Sarmad M. (2016). 'Introducing the CircOutlier package for identifying outliers in circular-circular regression', Andishe_ye Amari, 20(2), pp. 11-16.
CHICAGO
A. Ghazanfari Hissari & M. Sarmad, "Introducing the CircOutlier package for identifying outliers in circular-circular regression," Andishe_ye Amari, 20 2 (2016): 11-16,
VANCOUVER
Ghazanfari Hissari A., Sarmad M. Introducing the CircOutlier package for identifying outliers in circular-circular regression. Andishe_ye Amari. 2016;20(2):11-16 (In Persian).
