1. Procedure for Detecting Outliers in a Circular Regression Model.
- Author
-
Rambli, Adzhar, Abuzaid, Ali H. M., Mohamed, Ibrahim Bin, and Hussin, Abdul Ghapor
- Subjects
OUTLIERS (Statistics) ,REGRESSION analysis ,TRIGONOMETRIC functions ,ITERATIVE methods (Mathematics) ,MAXIMUM likelihood statistics - Abstract
A number of circular regression models have been proposed in the literature. In recent years, there is a strong interest shown on the subject of outlier detection in circular regression. An outlier detection procedure can be developed by defining a new statistic in terms of the circular residuals. In this paper, we propose a new measure which transforms the circular residuals into linear measures using a trigonometric function. We then employ the row deletion approach to identify observations that affect the measure the most, a candidate of outlier. The corresponding cut-off points and the performance of the detection procedure when applied on Down and Mardia’s model are studied via simulations. For illustration, we apply the procedure on circadian data. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF