Detection of outliers in simple circular regression models using the mean circular error statistic

Mohamed, I. and Abuzaid, A.H. and Hussin, A.G. (2013) Detection of outliers in simple circular regression models using the mean circular error statistic. Journal of Statistical Computation and Simulation, 83 (2). pp. 269-277. ISSN 0094-9655

[img] PDF
Detection_of_outliers_in_simple_circular_regression_models_using.pdf - Published Version
Restricted to Repository staff only

Download (211kB) | Request a copy

Abstract

The investigation on the identification of outliers in linear regression models can be extended to those for circular regression case. In this paper, we propose a new numerical statistic called mean circular error to identify possible outliers in circular regression models by using a row deletion approach. Through intensive simulation studies, the cut-off points of the statistic are obtained and its power of performance investigated.It is found that the performance improves as the concentration parameter of circular residuals becomes larger or the sample size becomes smaller. As an illustration, the statistic is applied to a wind direction data set.

Item Type: Article
Additional Information: Institute of Mathematical Sciences, University of Malaya
Uncontrolled Keywords: Circular distance; circular regression model; mean circular error; outlier; row deletion
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Institute of Mathematical Sciences
Depositing User: Ms. Izzan Ramizah Idris
Date Deposited: 13 Nov 2014 04:12
Last Modified: 13 Nov 2014 04:12
URI: http://eprints.um.edu.my/id/eprint/10160

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year