A Class of Nonparametric Density Derivative Estimators Based on Global Lipschitz Conditions
In: Essays in Honor of Aman Ullah
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- 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.
References listed on IDEAS
- Kairat Mynbaev & Carlos Martins-Filho, 2010.
"Bias reduction in kernel density estimation via Lipschitz condition,"
Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(2), pages 219-235.
- Mynbaev, Kairat & Martins-Filho, Carlos, 2009. "Bias reduction in kernel density estimation via Lipschitz condition," MPRA Paper 24904, University Library of Munich, Germany.
- 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.
- Singh, Radhey S., 1987. "Mise of kernel estimates of a density and its derivatives," Statistics & Probability Letters, Elsevier, vol. 5(2), pages 153-159, March.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- 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.
More about this item
KeywordsNonparametric derivative estimation; Lipschitz conditions; 62G07; 62G20; C14; C18;
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
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