0000000000976346
AUTHOR
Caroline Peltier
showing 2 related works from this author
Principal component analysis versus canonical variate analysis. For the analysis of sensory profiles. Meta-analysis of 387 sensory datasets
2013
International audience; Principal Component Analysis (PCA) of product mean scores is generally used to generate a product map from sensory profiling data. This approach does not take into account variance of these product mean scores due to individual variability. Canonical Variate Analysis (CVA) of the product effect in the two-way (product*panelist) multivariate ANOVA model is the natural extension of the classical univariate approach. This analysis generates successive components maximizing the ANOVA F-criterion. However, CVA requests the inversion of a covariance matrix which can result in computing instability when the sensory attributes are highly correlated. The paper compares result…
Mapping products with the CVAS R-package
2016
Mapping products with the CVAS R-package. AgroStat 2016 Congress - 14. Symposium on Statistical Methods for the Food Industry