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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| Date: | 2008 |
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| Main Author: | |
| Format: | Article |
| Language: | English |
| Published: |
Інститут математики НАН України
2008
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| Online Access: | http://dspace.nbuv.gov.ua/handle/123456789/4542 |
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| Journal Title: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Cite this: | 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| Summary: | 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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