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Restricted Inference in Circular-Linear and Linear-Circular Regression

Authors:

Thelge Buddika Peiris ,

Department of Mathematical Sciences, Worcester Polytechnic Institute, US
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Sungsu Kim

Division of Statistics, Northern Illinois University, US
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Abstract

In this paper, we investigate restricted inference on two types of circular regression, called circular-linear and linear-circular. Our aim in this paper is to propose an alternative method which is necessary to apply where one observes a weak association between circular dependent and linear predictor variables, or between linear dependent and circular predictor variables, having clear knowledge about the sign of slope. We illustrate that restricted inference is particularly useful for those circular regressions, which is due to weak association. Comparison between our proposed restricted inference and the unrestricted inference are given by using two examples, one from ecological study and the other from environmental study
DOI: http://doi.org/10.4038/sljastats.v17i1.7844
How to Cite: Peiris, T.B. & Kim, S., (2016). Restricted Inference in Circular-Linear and Linear-Circular Regression. Sri Lankan Journal of Applied Statistics. 17(1), pp.39–50. DOI: http://doi.org/10.4038/sljastats.v17i1.7844
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Published on 28 Apr 2016.
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