До відкриття латентного бінарного фактора в статистичних даних категорного типу

For a discrete model with tree-like structure, we demonstrate that if a separating variable (a root vertex) is binary, then constraints (like “tetrad difference”) hold. Specifically, when there are four or three manifest variables in a model, the “ditetrad-constraint” or “triad-constraint”, respect...

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Bibliographic Details
Date:2008
Main Authors: Андон, П.І., Балабанов, О.С.
Format: Article
Language:Ukrainian
Published: Видавничий дім "Академперіодика" НАН України 2008
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Online Access:https://nasplib.isofts.kiev.ua/handle/123456789/5822
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Journal Title:Digital Library of Periodicals of National Academy of Sciences of Ukraine
Cite this:До відкриття латентного бінарного фактора в статистичних даних категорного типу / П. I. Андон, О.С. Балабанов // Доп. НАН України. — 2008. — № 9. — С. 37-43. — Бібліогр.: 13 назв. — укр.

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Digital Library of Periodicals of National Academy of Sciences of Ukraine
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Summary:For a discrete model with tree-like structure, we demonstrate that if a separating variable (a root vertex) is binary, then constraints (like “tetrad difference”) hold. Specifically, when there are four or three manifest variables in a model, the “ditetrad-constraint” or “triad-constraint”, respectively, applies. So, these constraints facilitate the discovery of a hidden binary variable (latent class) which is responsible for associations among discrete manifest variables.
ISSN:1025-6415