A hierarchy of models for analysing sensory data

We propose a hierarchy of models for averaging sensory profile data. The models follow from formulating the data from each assessor in terms of association matrices and considering different strategies for weighted averaging of these matrices. It turns out that two forms of weighting contained within the hierarchy are very close to Generalised Procrustes Analysis (GPA) and Individual Differences Scaling (INDSCAL). The advantage of the current approach is that the methods are not iterative. The methods are illustrated using data based on perception of yoghurts.