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A comparison of generalised procrustes analysis and multiple factor analysis for projective mapping data
O. Tomic, I. Berget,
Tormod Næs
Food Analytics and Biotechnology
20
Citations (Scopus)
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Dive into the research topics of 'A comparison of generalised procrustes analysis and multiple factor analysis for projective mapping data'. Together they form a unique fingerprint.
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Keyphrases
Block Method
33%
Generalized Procrustes Analysis
100%
Mapping Data
100%
Monte Carlo Simulation
33%
Multiple Factor Analysis
100%
Multivariate Statistical Techniques
33%
Napping®
66%
Projective Mapping
100%
RV Coefficient
33%
Mathematics
Factor Analysis
100%
Monte Carlo
33%
Projective
100%
Real Data
66%
Simulated Data
33%
Statistical Method
33%
Engineering
Assessor
50%
Real Data
100%
Similarity
50%
Simulated Data
50%
Neuroscience
Individual Differences
100%
Monte Carlo Method
100%
Earth and Planetary Sciences
Data Transmission
33%
Factor Analysis
100%
Food Science
Generalized Procrustes Analysis
100%