Inversion Theorem Based Kernel Density Estimation for the Ordinary Least Squares Estimator of a Regression Coefficient.

@article{Wang2015InversionTB,
  title={Inversion Theorem Based Kernel Density Estimation for the Ordinary Least Squares Estimator of a Regression Coefficient.},
  author={Dongliang Wang and Alan D. Hutson},
  journal={Communications in statistics: theory and methods},
  year={2015},
  volume={44 8},
  pages={
          1571-1579
        }
}
The traditional confidence interval associated with the ordinary least squares estimator of linear regression coefficient is sensitive to non-normality of the underlying distribution. In this article, we develop a novel kernel density estimator for the ordinary least squares estimator via utilizing well-defined inversion based kernel smoothing techniques in order to estimate the conditional probability density distribution of the dependent random variable. Simulation results show that given a… CONTINUE READING

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