An asymptotic theory for semiparametric generalized least squares estimation in partially linear regression models |
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| Authors: | Gemai Chen Jinhong You |
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| Institution: | (1) Department of Mathematics and Statistics, University of Calgary, T2N 1N4 Calgary, Alberta, Canada;(2) Department of Biostatistics, University of North Carolina at Chapel Hill, 27599-7400 Chapel Hill, NC, USA |
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| Abstract: | Consider a partially linear regression model with an unknown vector parameter β, an unknown functiong(·), and unknown heteroscedastic error variances. In this paper we develop an asymptotic semiparametric generalized least
squares estimation theory under some weak moment conditions. These moment conditions are satisfied by many of the error distributions
encountered in practice, and our theory does not require the number of replications to go to infinity. |
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| Keywords: | Heteroscedasticity partially linear regression model semiparametric generalized least squares estimator |
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