Enhancing the distance minimization methods of matrix updating within a homothetic paradigm

Abstract Matrix updating methods are used for constructing the target matrix with the prescribed row and column marginal totals that demonstrates the highest possible level of its structural similarity to initial matrix given. A concept of structural similarity has a vague framework that can be slig...

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Main Author: Vladimir Motorin
Format: Article
Language:English
Published: SpringerOpen 2017-11-01
Series:Journal of Economic Structures
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40008-017-0094-7
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spelling doaj-d9284f246a544896bb2d2d0403f61ed22020-11-25T00:39:41ZengSpringerOpenJournal of Economic Structures2193-24092017-11-016112210.1186/s40008-017-0094-7Enhancing the distance minimization methods of matrix updating within a homothetic paradigmVladimir Motorin0Laboratory for Research in Inflation and Growth, Expert Institute, National Research University Higher School of EconomicsAbstract Matrix updating methods are used for constructing the target matrix with the prescribed row and column marginal totals that demonstrates the highest possible level of its structural similarity to initial matrix given. A concept of structural similarity has a vague framework that can be slightly refined under considering a particular case of strict proportionality between row and column marginal totals for target and initial matrices. Here the question arises: can we accept the initial matrix homothety as optimal solution for proportionality case of matrix-updating problem? In most practical situations, an affirmative answer to the question is almost obvious. It is natural to call this common notion by homothetic paradigm and to refer its checking as homothetic testing. Some well-known methods for matrix updating serve as an additional instrumental confirmation to validity of homothetic paradigm. It is shown that RAS method and Kuroda’s method pass through the homothetic test successfully. Homothetic paradigm can be helpful for enhancing a collection of matrix updating methods based on constrained minimization of the distance functions. Main attention is paid to improving the methods with weighted squared differences (both regular and relative) as an objective function. As an instance of a incorrigible failure in the homothetic testing, the GRAS method for updating the economic matrices with some negative entries is analyzed in details. A collection of illustrative numerical examples and some recommendations for method’s choice are given.http://link.springer.com/article/10.1186/s40008-017-0094-7Matrix updating methodsHomothetic paradigm and testingRAS and Kuroda’s methodsKullback–Leibler divergenceMethods of weighted squared differencesGRAS method
collection DOAJ
language English
format Article
sources DOAJ
author Vladimir Motorin
spellingShingle Vladimir Motorin
Enhancing the distance minimization methods of matrix updating within a homothetic paradigm
Journal of Economic Structures
Matrix updating methods
Homothetic paradigm and testing
RAS and Kuroda’s methods
Kullback–Leibler divergence
Methods of weighted squared differences
GRAS method
author_facet Vladimir Motorin
author_sort Vladimir Motorin
title Enhancing the distance minimization methods of matrix updating within a homothetic paradigm
title_short Enhancing the distance minimization methods of matrix updating within a homothetic paradigm
title_full Enhancing the distance minimization methods of matrix updating within a homothetic paradigm
title_fullStr Enhancing the distance minimization methods of matrix updating within a homothetic paradigm
title_full_unstemmed Enhancing the distance minimization methods of matrix updating within a homothetic paradigm
title_sort enhancing the distance minimization methods of matrix updating within a homothetic paradigm
publisher SpringerOpen
series Journal of Economic Structures
issn 2193-2409
publishDate 2017-11-01
description Abstract Matrix updating methods are used for constructing the target matrix with the prescribed row and column marginal totals that demonstrates the highest possible level of its structural similarity to initial matrix given. A concept of structural similarity has a vague framework that can be slightly refined under considering a particular case of strict proportionality between row and column marginal totals for target and initial matrices. Here the question arises: can we accept the initial matrix homothety as optimal solution for proportionality case of matrix-updating problem? In most practical situations, an affirmative answer to the question is almost obvious. It is natural to call this common notion by homothetic paradigm and to refer its checking as homothetic testing. Some well-known methods for matrix updating serve as an additional instrumental confirmation to validity of homothetic paradigm. It is shown that RAS method and Kuroda’s method pass through the homothetic test successfully. Homothetic paradigm can be helpful for enhancing a collection of matrix updating methods based on constrained minimization of the distance functions. Main attention is paid to improving the methods with weighted squared differences (both regular and relative) as an objective function. As an instance of a incorrigible failure in the homothetic testing, the GRAS method for updating the economic matrices with some negative entries is analyzed in details. A collection of illustrative numerical examples and some recommendations for method’s choice are given.
topic Matrix updating methods
Homothetic paradigm and testing
RAS and Kuroda’s methods
Kullback–Leibler divergence
Methods of weighted squared differences
GRAS method
url http://link.springer.com/article/10.1186/s40008-017-0094-7
work_keys_str_mv AT vladimirmotorin enhancingthedistanceminimizationmethodsofmatrixupdatingwithinahomotheticparadigm
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