Mynbaev, Kairat and Martins-Filho, Carlos (2009): Bias reduction in kernel density estimation via Lipschitz condition. Published in: Journal of Nonparametric Statistics , Vol. 22, No. 2 (February 2010): pp. 219-235.
Martins-Filho, Carlos and yang, ke (2007): Finite sample performance of kernel-based regression methods for non-parametric additive models under common bandwidth selection criterion. Published in: Journal of Nonparametric Statistics , Vol. 19, No. 1 (2007): pp. 23-62.
Mynbaev, Kairat and Martins-Filho, Carlos (2015): Consistency and asymptotic normality for a nonparametric prediction under measurement errors. Published in: Journal of Multivariate Analysis , Vol. 139, (2015): pp. 166-188.
Mynbaev, Kairat and Martins-Filho, Carlos (2016): Reducing bias in nonparametric density estimation via bandwidth dependent kernels: L1 view. Forthcoming in: Statistics and Probability Letters , Vol. 123, (2017): pp. 17-22.
Mynbaev, Kairat and Martins-Filho, Carlos and Aipenova, Aziza (2015): A class of nonparametric density derivative estimators based on global Lipschitz conditions. Published in: Advances in Econometrics , Vol. 36, No. Essays in Honor of Aman Ullah (2016): pp. 591-615.
Mynbayev, Kairat and Martins-Filho, Carlos (2017): Unified estimation of densities on bounded and unbounded domains. Published in: Annals of the Institute of Statistical Mathematics No. https://doi.org/10.1007/s10463-018-0663-z (2018): pp. 1-35.
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