A sampling algorithm for bandwidth estimation in an nonparametric regression model with a flexible error density
The unknown error density of a nonparametric regression model is approximated by a mixture of Gaussian densities with means being the individual error realizations and variance a constant parameter. Such a mixture density has the form of a kernel density
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