Least circular distance regression for directional data

Ulric Lund

Journal of Applied Statistics, 1999, vol. 26, issue 6, 723-733

Abstract: Least-squares regression is not appropriate when the response variable is circular, and can lead to erroneous results. The reason for this is that the squared difference is not an appropriate measure of distance on the circle. In this paper, a circular analog to least-squares regression is presented for predicting a circular response variable by another circular variable and a set of linear covariates. An alternative maximum-likelihood formulation yields the same regression parameter estimates. Under the maximum-likelihood model, asymptotic standard errors of the parameter estimates are obtained. As an example, the regression model is used to model data from a marine biology study.

Date: 1999
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Citations: View citations in EconPapers (4)

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DOI: 10.1080/02664769922160

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