Bandwidth selection for kernel conditional density estimation
We consider bandwidth selection for the kernel estimator of conditional density with one explanatory variable. Several bandwidth selection methods are derived ranging from fast rules-of-thumb which assume the underlying densities are known to relatively slow procedures which use the bootstrap. The methods are compared and a practical bandwidth selection strategy which combines the methods is proposed. The methods are compared using two simulation studies and a real data set.
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- Hyndman, R.J. & Yao, Q., 1998.
"Nonparametric Estimation and Symmetry Tests for Conditional Density Functions,"
Monash Econometrics and Business Statistics Working Papers
17/98, Monash University, Department of Econometrics and Business Statistics.
- Yao, Qiwei & Hyndman, Rob J., 2002. "Nonparametric estimation and symmetry tests for conditional density functions," LSE Research Online Documents on Economics 6092, London School of Economics and Political Science, LSE Library.
- Hall, Peter & Wolff, Rodney C. L. & Yao, Qiwei, 1999. "Methods for estimating a conditional distribution function," LSE Research Online Documents on Economics 6631, London School of Economics and Political Science, LSE Library.
- Fan, Jianqing & Yao, Qiwei & Tong, Howell, 1996. "Estimation of conditional densities and sensitivity measures in nonlinear dynamical systems," LSE Research Online Documents on Economics 6704, London School of Economics and Political Science, LSE Library. Full references (including those not matched with items on IDEAS)
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