Estimation in an implicit multivariate measurement error model with clustering in the regressor

An implicit linear multivariate model DZ ≈ 0 is considered, where the data matrix D is observed with errors, and Z is a parameter matrix. The error matrix is partitioned into two uncorrelated blocks, and the total covariance structure in each block is supposed to be known up to a corresponding scala...

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Дата:2008
Автор: Polekha, M.
Формат: Стаття
Мова:Англійська
Опубліковано: Інститут математики НАН України 2008
Онлайн доступ:https://nasplib.isofts.kiev.ua/handle/123456789/4542
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Назва журналу:Digital Library of Periodicals of National Academy of Sciences of Ukraine
Цитувати:Estimation in an implicit multivariate measurement error model with clustering in the regressor / M. Polekha // Theory of Stochastic Processes. — 2008. — Т. 14 (30), № 1. — С. 117–125. — Бібліогр.: 9 назв.— англ.

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Digital Library of Periodicals of National Academy of Sciences of Ukraine
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author Polekha, M.
author_facet Polekha, M.
citation_txt Estimation in an implicit multivariate measurement error model with clustering in the regressor / M. Polekha // Theory of Stochastic Processes. — 2008. — Т. 14 (30), № 1. — С. 117–125. — Бібліогр.: 9 назв.— англ.
collection DSpace DC
description An implicit linear multivariate model DZ ≈ 0 is considered, where the data matrix D is observed with errors, and Z is a parameter matrix. The error matrix is partitioned into two uncorrelated blocks, and the total covariance structure in each block is supposed to be known up to a corresponding scalar factor. Moreover, the row data are clustered into two groups. Based on the method of corrected objective function, the strongly consistent estimators of scalar factors and the kernel of the matrix D are constructed, as the numbers of rows in the clusters tend to infinity.
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spelling Polekha, M.
2009-11-25T11:07:39Z
2009-11-25T11:07:39Z
2008
Estimation in an implicit multivariate measurement error model with clustering in the regressor / M. Polekha // Theory of Stochastic Processes. — 2008. — Т. 14 (30), № 1. — С. 117–125. — Бібліогр.: 9 назв.— англ.
0321-3900
https://nasplib.isofts.kiev.ua/handle/123456789/4542
519.21
An implicit linear multivariate model DZ ≈ 0 is considered, where the data matrix D is observed with errors, and Z is a parameter matrix. The error matrix is partitioned into two uncorrelated blocks, and the total covariance structure in each block is supposed to be known up to a corresponding scalar factor. Moreover, the row data are clustered into two groups. Based on the method of corrected objective function, the strongly consistent estimators of scalar factors and the kernel of the matrix D are constructed, as the numbers of rows in the clusters tend to infinity.
en
Інститут математики НАН України
Estimation in an implicit multivariate measurement error model with clustering in the regressor
Article
published earlier
spellingShingle Estimation in an implicit multivariate measurement error model with clustering in the regressor
Polekha, M.
title Estimation in an implicit multivariate measurement error model with clustering in the regressor
title_full Estimation in an implicit multivariate measurement error model with clustering in the regressor
title_fullStr Estimation in an implicit multivariate measurement error model with clustering in the regressor
title_full_unstemmed Estimation in an implicit multivariate measurement error model with clustering in the regressor
title_short Estimation in an implicit multivariate measurement error model with clustering in the regressor
title_sort estimation in an implicit multivariate measurement error model with clustering in the regressor
url https://nasplib.isofts.kiev.ua/handle/123456789/4542
work_keys_str_mv AT polekham estimationinanimplicitmultivariatemeasurementerrormodelwithclusteringintheregressor