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
- repec:taf:gnstxx:v:22:y:2010:i:2:p:219-235 is not listed on IDEAS
- 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.
- 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.
- 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.
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- 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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