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Semi-parametric estimation tn the nonlinear structural errors-in-variables model
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DOI：10.1214/aos/996986502.png)
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摘要
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In the nonlinear structural errors-in-variables model, we propose a consistent estimator of the unknown parameter using a modified least squares criterion. We give an upper bound of its rate of convergence which is strongly related to the regularity of the regression function and is generally slower than the parametric rate of convergence n(-1/2). Nevertheless, the rate is of order n-(1/2) for some particular analytic regression functions. For instance, when the regression Function is either a polynomial function or an exponential function, we prove that our estimator achieves the parametric rate of convergence.
Keyword:
semi-parametric estimation
analytic function
Fourier transform
errors-in-variables model
nonparametric estimation
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期刊
IF:
3.7
论文数:
2.8K
被引数:
2.9W
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