Strong Consistency of Estimators for Heteroscedastic Partly Linear Regression Model under Dependent Samples
In this paper we are concerned with the heteroscedastic regression model under correlated errors , where it is assumed that , the design points are known and nonrandom, and and are unknown functions. The interest lies in the slope parameter . Assuming the unobserved disturbance are negatively associated, we study the issue of strong consistency for two different slope estimators: the least squares estimator and the weighted least squares estimator.
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