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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/11035
Title: Minimum distance from point to linear variety in Euclidean space of the two-dimensional matrices
Authors: Mukha, V. S.
Keywords: публикации ученых;linear variety;approximation of multidimensional statistical data;perpendicular distances
Issue Date: 2016
Publisher: Minsk
Citation: Mukha, V. S. Minimum distance from point to linear variety in Euclidean space of the two-dimensional matrices / V. S. Mukha // Computer Data Analysis and Modeling. Theoretical and applied stochastics. Proceedings of the XI International Conference (Minsk, September 6 – 10, 2016). – Minsk: Publishing center of BSU, 2016. – P. 218 – 221.
Abstract: This work relates to the problem of linear approximation of multidimensional statistical data. Instead of the approach of regression analysis, we want to use another approach which is to minimize of the sum of the squares of the per-pendicular distances from the system of points to the approximating plane. We receive the formula of minimum distance from point to linear variety in Euclidean space of the two-dimensional matrices as a first step in solving the problem.
URI: https://libeldoc.bsuir.by/handle/123456789/11035
Appears in Collections:Публикации в изданиях Республики Беларусь

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