Asymptotically independent estimators in a structural linear model with measurement errors
We consider a structural linear regression model with measurement errors. A new parameterization is proposed, in which the expectation of the response variable plays the role of a new parameter instead of the intercept. This enables us to form three groups of asymptotically independent estimators in...
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| Дата: | 2016 |
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| Автори: | , , , , , |
| Формат: | Стаття |
| Мова: | Українська |
| Опубліковано: |
Institute of Mathematics, NAS of Ukraine
2016
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| Онлайн доступ: | https://umj.imath.kiev.ua/index.php/umj/article/view/1937 |
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| Назва журналу: | Ukrains’kyi Matematychnyi Zhurnal |
| Завантажити файл: |  |
Репозитарії
Ukrains’kyi Matematychnyi Zhurnal| Резюме: | We consider a structural linear regression model with measurement errors. A new parameterization is proposed, in which
the expectation of the response variable plays the role of a new parameter instead of the intercept. This enables us to form
three groups of asymptotically independent estimators in the case where the ratio of variances of the errors is known and
two groups of this kind if the variance of the measurement error in the covariate is known. In this case, it is not assumed
that the errors and the latent variable are normally distributed. |
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