Multivariate-multiple circular regression

Article Type

Research Article

Publication Title

Journal of Statistical Computation and Simulation

Abstract

We introduce a fully model-based approach of studying functional relationships between a multivariate circular-dependent variable and several circular covariates, enabling inference regarding all model parameters and related prediction. Two multiple circular regression models are presented for this approach. First, for an univariate circular-dependent variable, we propose the least circular mean-square error (LCMSE) estimation method, and asymptotic properties of the LCMSE estimators and inferential methods are developed and illustrated. Second, using a simulation study, we provide some practical suggestions for model selection between the two models. An illustrative example is given using a real data set from protein structure prediction problem. Finally, a straightforward extension to the case with a multivariate-dependent circular variable is provided.

First Page

1277

Last Page

1291

DOI

10.1080/00949655.2016.1261292

Publication Date

5-3-2017

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