Statistics cluster

Variation with time Advanced statistics Cluster analysis... 

To further strengthen decision-making, it is helpful to use statistical clustering to place each experimental compound in the context of a database created from the pharmaceutical profiling of compounds with well-characterized human PK. In the absence of... 

Metabolomics techniques can also be used as a quality control for complex natural products mixtures. Recently, NMR combined with PCA statistical clustering was applied to monitor the quality of claimed antimalarial herbal remedies. The authors demonstrate that the products incorporating Artemisia afra or A. annua could be distinguished and that the bioactive artemisinin was an important discriminant factor.40... 

Then Family used the version of the Flory theory proposed by Isaacson and Lubensky [78] for determination of the fractal dimension of an isolated statistical cluster. The method is based on the determination of the most probable cluster conformation using the free energy of repulsion. Under the influence of elastic free energy, the radius of the real cluster tends to the radius of the ideal cluster that involves no repulsive interaction. 

For a purely statistical fractal for which D = 4, we obtain = 4. This means that this type of statistical cluster is compact up to d = 4. Therefore, Family [9] called this state of statistical fractals the collapsed state. 

Most statistical clustering methods are memory intensive and are simply unwieldy if the data set is too large. Also, some methods rely on assumptions (normal distribution, etc.) about data in forming clusters. So, if your data set is large or if it does not meet the necessary assumptions you may be better off using an ANN. 

A module of a product is a cluster of functions and components that are operationally self-contained. Such clusters can be created in multiple ways quality function deployment (QFD), design structure matrix (DSM), statistical clustering, and... 

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