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Classification of Fermentation Performance by Multivariate Analysis Based on Mean Hypothesis Testing

Journal of Bioscience and Bioengineering, 2002
Multivariate analysis, such as principal component analysis and artificial autoassociative neural networks, is currently extensively applied to feature capturing, physiological state recognition, fault detection and bioprocess control. However, it is not clear which process variable should be selected as an important input for multivariate analysis to ...
Jihua, Huang   +4 more
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A multivariate analysis of Pleistocene hominids: testing hypotheses of European origins

Journal of Human Evolution, 1997
Multivariate analysis of intra- and inter-group variability in Middle and Upper Pleistocene human remains, based on facial traits, show close affinities between Upper Palaeolithic and Mesolithic samples, which are clearly distinct from Lower Palaeolithic and Neanderthal samples.
D, Turbón   +2 more
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Testing the central market hypothesis: a multivariate analysis of Tanzanian sorghum markets

Agricultural Economics, 2011
AbstractThe central market hypothesis is important in the analysis of market integration because it implies a specific market structure while avoiding a simultaneity problem. However, despite its importance, the central market hypothesis is difficult to test and is therefore often assumed.
Frank Asche   +2 more
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Frequency Domain Causality Analysis Method for Multivariate Systems in Hypothesis Testing Framework

IFAC Proceedings Volumes, 2014
Abstract A variety of causality analysis methods have been proposed and used for complex large multivariate systems. In the frequency domain, partial directed coherence (PDC) is an important method. We expect that the frequency domain methods can provide a more detailed explanation of causal influence over different frequencies, but PDC provides no ...
Jing Zhang   +4 more
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