Abstract
A variety of models have been proposed to accommodate data involving directional vectors in two-dimensions, with no identified start or end point. By convention such directions are represented by points in the interval (0,π). Data of this kind is called axial data. A survey of symmetric and asymmetric models for axial data is provided here. In addition, for certain models, parametric inference issues are addressed. In some cases, bivariate and multivariate extensions are readily envisioned.
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© 2011 Springer-Verlag Berlin Heidelberg
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Arnold, B.C., SenGupta, A. (2011). Models for Axial Data. In: Wells, M., SenGupta, A. (eds) Advances in Directional and Linear Statistics. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2628-9_1
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DOI: https://doi.org/10.1007/978-3-7908-2628-9_1
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Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-2627-2
Online ISBN: 978-3-7908-2628-9
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