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Asymptotic normality of estimators in heteroscedastic errors-in-variables model. (English) Zbl 1443.62210

Summary: This article is concerned with the estimating problem of heteroscedastic partially linear errors-in-variables models. We derive the asymptotic normality for estimators of the slope parameter and the nonparametric component in the case of known error variance with stationary \(\alpha\)-mixing random errors. Also, when the error variance is unknown, the asymptotic normality for the estimators of the slope parameter and the nonparametric component as well as variance function is considered under independent assumptions. Finite sample behavior of the estimators is investigated via simulations too.

MSC:

62J12 Generalized linear models (logistic models)
62E20 Asymptotic distribution theory in statistics
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