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Analysis of the quality of approximations in the statistical analysis of multivariate observations
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Fördergeber - Sonstige;
We consider high-dimension low-sample-size data taken from the standard multivariate normal distribution under assumption that dimension of the vectors is a random variable. Three geometric statistics of the normal vectors are investigated, the length of a observation vector, the difference between any two independent observation vectors and the angle between these vectors at the population mean. The second order Chebyshev-Edgeworth expansions for distributions of these geometric statistics are constructed with error bounds. The poject continues studies on approximation of statistics for random size samples.
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