Optimal experimental design to estimate the correlation coefficient in a gaussian model
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The article considers the problem of finding the distribution function of the components of a stochastic finite-dimensional vector from nonsimultaneous observations of the vector components. An experimental procedure is proposed in which the observation process is related with some instrumental random variable distributed independently of the experimentally observed vector, and the relationship between the two variables is chosen in an optimal manner. The optimal control distribution minimizes the correlation coefficients of the observed vector components. The minimization problem is solved and an optimal experimental procedure is described.
KeywordsMathematical Modeling Distribution Function Computational Mathematic Industrial Mathematic Minimization Problem
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