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Procrustes analysis is a technique of comparing the alternative geometrical representations of a group of multivariate data or of the proximity matrix, for instance, two competing multidimensional scaling solutions for the latter. The two solutions are compared to each other using a residual sum of the squares criterion, which is minimized by permitting the coordinates corresponding to one solution to be rotated, reflected and translated relative to other. Generalized Procrustes analysis permits comparison of more than two alternative solutions by at the same time translating, rotating and reflecting them so as to optimize the predefined goodness-of-fit measure.
Kaiser's rule is the rule frequently used in the principal components analysis for selecting the suitable the number of components. When the components are derived from correlati
High-dimensional data : This term used for data sets which are characterized by the very large number of variables and a much more modest number of the observations. In the 21 st
need answers to questions in book advanced and multivariate statistical methods
Reinterviewing is the second interview for a sample of survey respondents in which questions of the original interview (or the subset of them) are repeated again. The same methods
The transformation of the Pearson's product moment correlation coefficient, r, can be given by The statistic z has the normal distribution with mean here ρ is the pop
A metal fabrication process uses a die-cast metal fastener at a uniform rate of 300 units per year. Currently, this item is currently purchased from an external supplier at a unit
It is an informal method of assessing the effect of the publication bias, generally in the context of the meta-analysis. The effect measures from each of the reported study are plo
Conjugate prior : The distribution for samples from the particular probability distribution such that the posterior distribution at each stage of the sampling is of the identical f
The functions of the data and the parameters of interest which can be brought in use to conduct inference about the parameters when full distribution of the observations is unknown
Nearest-neighbour methods are the methods of discriminant analysis are based on studying the training set subjects much similar to the subject to be classified. Classification mig
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