9 resultados para multivariate normality

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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Rhesus macaques and stump-tailed macaques are sympatric in western Yunnan (China), coexisting or occupying habitats that show little difference. This paper tests hypotheses based on theoretical expectation from the differing biomechanical demands of terrestrial and arboreal quadrupedalism in stump-tailed macaques and rhesus macaques, respectively. Individuals of these two macaque taxa were markedly separated by the first two principal components and discriminant analyses based on 18 variables of the upper limb. The rhesus macaques appear to be more adapted for arboreal quadruped habits because of elongation of the clavicle and forearm, a larger humeral head and greater midshaft sagittal diameters of the radius and ulna.

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The optimization of the organic modifier concentration in micellar electrokinetic capillary chromatography (MECC) has been achieved by a uniform design and iterative optimization method, which has been developed for the optimization of composition of the mobile phase in high performance liquid chromatography. According to the proposed method, the uniform design technique has been applied to design the starting experiments, which can reduce the number of experiments compared with traditional simultaneous methods, such as the orthano design. The hierarchical chromatographic response function has been modified to evaluate the separation quality of a chromatogram in MECC. An iterative procedure has been adopted to search the optimal concentration of organic modifiers for improving the accuracy of retention predicted and the quality of the chromatogram. Validity of the optimization method has been proved by the separation of 31 aromatic compounds in MECC. (C) 2000 John Wiley & Sons, Inc.

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Multivariate classification methods were used to evaluate data on the concentrations of eight metals in human senile lenses measured by atomic absorption spectrometry. Principal components analysis and hierarchical clustering separated senile cataract lenses, nuclei from cataract lenses, and normal lenses into three classes on the basis of the eight elements. Stepwise discriminant analysis was applied to give discriminant functions with five selected variables. Results provided by the linear learning machine method were also satisfactory; the k-nearest neighbour method was less useful.