Stochastic regression model with dependent disturbances (Q2740103)
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scientific article; zbMATH DE number 1646504
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Stochastic regression model with dependent disturbances |
scientific article; zbMATH DE number 1646504 |
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16 September 2001
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stochastic regression models
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short-memory processes
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long- memory processes
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best linear unbiased estimators
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least squares estimators
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ratio estimators
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spectral density
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stationary linear processes
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0.9451653
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0.8726293
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0.87158024
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0.86786985
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0.8647762
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0.8636806
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Stochastic regression model with dependent disturbances (English)
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The authors consider the stochastic regression model NEWLINE\[NEWLINEy_t=\beta x_t+u_t,\;t=1,2,...,NEWLINE\]NEWLINE where both the regressor \(\{x_t\}\) and the unobservable error \(\{u_t\}\) are stochastic processes, and \(\beta\) is an unknown parameter. Various cases where \(\{x_t\}\) and \(\{u_t\}\) are short or long memory dependent are considered. The asymptotic theory for estimators of the parameter \(\beta\) is derived. Numerical studies are given.
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