A Monte Carlo comparison of parametric and nonparametric quantile regressions
This study compares parametric and nonparametric quantile regression methods using Monte Carlo simulations. Simulation results indicate that the nonparametric quantile regression approach is more appropriate, particularly when the underlying model is nonlinear or the error term follows a non-normal distribution.
Year of publication: |
2004
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Authors: | Min, Insik ; Kim, Inchul |
Published in: |
Applied Economics Letters. - Taylor & Francis Journals, ISSN 1350-4851. - Vol. 11.2004, 2, p. 71-74
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Publisher: |
Taylor & Francis Journals |
Saved in:
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