Ejemplares similares: A class of nonparametric density derivative estimators based on global Lipschitz conditions
- Bias reduction in kernel density estimation via Lipschitz condition
- Reducing bias in nonparametric density estimation via bandwidth dependent kernels: L1 view
- Consistency and asymptotic normality for a nonparametric prediction under measurement errors
- A class of improved parametrically guided nonparametric regression estimators
- A smooth nonparametric conditional quantile frontier estimator
- High-order conditional quantile estimation based on nonparametric models of regression
Autor: Mynbaev, Kairat
- A class of nonparametric density derivative estimators based on global Lipschitz conditions
- Bias reduction in kernel density estimation via Lipschitz condition
- Reducing bias in nonparametric density estimation via bandwidth dependent kernels: L1 view
- Consistency and asymptotic normality for a nonparametric prediction under measurement errors
Autor: Martins-Filho, Carlos
- Local exponential frontier estimation
- Nonparametric estimation of conditional value-at-risk and expected shortfall based on extreme value theory
- A class of nonparametric density derivative estimators based on global Lipschitz conditions
- A comparison of nonparametric efficiency estimators: DEA, FDH, DEAC, FDHC, order-m and quantile
- Bias reduction in kernel density estimation via Lipschitz condition
- A smooth nonparametric conditional quantile frontier estimator