Curved axes and trajectories for multidimensional scaling, with applications to sensory and consumer data


John Bennett, Stephen (2008) Curved axes and trajectories for multidimensional scaling, with applications to sensory and consumer data. PhD thesis, University of Liverpool.

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Abstract

The analysis of sensory and consumer-derived data involves the use of many different statistical techniques. The vast majority of these are multivariate in for example, multidimensional scaling (MDS) and biplots. However, univariate techniques such as repeated measures analysis of variance and the Bradley-Terry model for paired comparison data are also common. This thesis introduces enhancements to MDS based on the use of curved axes and trajectories.

Item Type: Thesis (PhD)
Depositing User: Symplectic Admin
Date Deposited: 20 Oct 2023 09:24
Last Modified: 20 Oct 2023 09:46
DOI: 10.17638/03174399
Copyright Statement: Copyright © and Moral Rights for this thesis and any accompanying data (where applicable) are retained by the author and/or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge
URI: https://livrepository.liverpool.ac.uk/id/eprint/3174399
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