Bias reduction in kernel density estimation via Lipschitz condition
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DOI: 10.1080/10485250903266058
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- Mynbaev, Kairat & Martins-Filho, Carlos, 2009. "Bias reduction in kernel density estimation via Lipschitz condition," MPRA Paper 24904, University Library of Munich, Germany.
References listed on IDEAS
- Lejeune, Michel & Sarda, Pascal, 1992. "Smooth estimators of distribution and density functions," Computational Statistics & Data Analysis, Elsevier, vol. 14(4), pages 457-471, November.
- Pagan,Adrian & Ullah,Aman, 1999.
"Nonparametric Econometrics,"
Cambridge Books,
Cambridge University Press, number 9780521355643, December.
- Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521586115, December.
- Marco Di Marzio, 2004. "Boosting kernel density estimates: A bias reduction technique?," Biometrika, Biometrika Trust, vol. 91(1), pages 226-233, March.
Citations
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Cited by:
- Kairat Mynbaev & Carlos Martins-Filho & Aziza Aipenova, 2016.
"A Class of Nonparametric Density Derivative Estimators Based on Global Lipschitz Conditions,"
Advances in Econometrics, in: Gloria GonzÁlez-Rivera & R. Carter Hill & Tae-Hwy Lee (ed.),Essays in Honor of Aman Ullah, volume 36, pages 591-615,
Emerald Publishing Ltd.
- Mynbaev, Kairat & Martins-Filho, Carlos & Aipenova, Aziza, 2015. "A class of nonparametric density derivative estimators based on global Lipschitz conditions," MPRA Paper 75909, University Library of Munich, Germany, revised 2014.
- Martins-Filho, Carlos & Ziegelmann, Flávio Augusto & Torrent, Hudson da Silva, 2013. "Local Exponential Frontier Estimation," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 33(2), November.
- Henderson, Daniel J. & Parmeter, Christopher F., 2012.
"Canonical higher-order kernels for density derivative estimation,"
Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1383-1387.
- Daniel J. Henderson & Christopher F. Parmeter, 2010. "Canonical Higher-Order Kernels for Density Derivative Estimation," Working Papers 2011-14, University of Miami, Department of Economics.
- Mynbaev, Kairat & Martins-Filho, Carlos, 2015.
"Consistency and asymptotic normality for a nonparametric prediction under measurement errors,"
Journal of Multivariate Analysis, Elsevier, vol. 139(C), pages 166-188.
- Mynbaev, Kairat & Martins-Filho, Carlos, 2015. "Consistency and asymptotic normality for a nonparametric prediction under measurement errors," MPRA Paper 75845, University Library of Munich, Germany, revised 2014.
- Kairat Mynbaev & Carlos Martins-Filho, 2019.
"Unified estimation of densities on bounded and unbounded domains,"
Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(4), pages 853-887, August.
- Mynbayev, Kairat & Martins-Filho, Carlos, 2017. "Unified estimation of densities on bounded and unbounded domains," MPRA Paper 87044, University Library of Munich, Germany, revised Jan 2018.
- Mynbaev, Kairat T. & Nadarajah, Saralees & Withers, Christopher S. & Aipenova, Aziza S., 2014.
"Improving bias in kernel density estimation,"
Statistics & Probability Letters, Elsevier, vol. 94(C), pages 106-112.
- Mynbaev, Kairat & Nadarajah, Saralees & Withers, Christopher & Aipenova, Aziza, 2014. "Improving bias in kernel density estimation," MPRA Paper 75846, University Library of Munich, Germany, revised 2014.
- Christopher Withers & Saralees Nadarajah, 2013. "Density estimates of low bias," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(3), pages 357-379, April.
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JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
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