Optimal bandwidth selection for multivariate kernel deconvolution density estimation
Author
Abstract
Suggested Citation
DOI: 10.1007/s11749-006-0027-5
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Delaigle, A. & Gijbels, I., 2004. "Practical bandwidth selection in deconvolution kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 249-267, March.
- Marron, James Stephen & Härdle, Wolfgang, 1986. "Random approximations to some measures of accuracy in nonparametric curve estimation," Journal of Multivariate Analysis, Elsevier, vol. 20(1), pages 91-113, October.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Guillermo Basulto-Elias & Alicia L. Carriquiry & Kris Brabanter & Daniel J. Nordman, 2021. "Bivariate Kernel Deconvolution with Panel Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 122-151, May.
- Roy, Arkaprava & Sarkar, Abhra, 2023. "Bayesian semiparametric multivariate density deconvolution via stochastic rotation of replicates," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Kuosmanen, Timo & Johnson, Andrew, 2017. "Modeling joint production of multiple outputs in StoNED: Directional distance function approach," European Journal of Operational Research, Elsevier, vol. 262(2), pages 792-801.
- Ali Al-Sharadqah & Majid Mojirsheibani & William Pouliot, 2020. "On the performance of weighted bootstrapped kernel deconvolution density estimators," Statistical Papers, Springer, vol. 61(4), pages 1773-1798, August.
- Crucinio, Francesca R. & De Bortoli, Valentin & Doucet, Arnaud & Johansen, Adam M., 2024. "Solving a class of Fredholm integral equations of the first kind via Wasserstein gradient flows," Stochastic Processes and their Applications, Elsevier, vol. 173(C).
- Delsol, Laurent & Ferraty, Frédéric & Vieu, Philippe, 2011. "Structural test in regression on functional variables," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 422-447, March.
- Timmermans, Catherine & Delsol, Laurent & von Sachs, Rainer, 2013. "Using Bagidis in nonparametric functional data analysis: Predicting from curves with sharp local features," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 421-444.
- Parmeter, Christopher F., 2008. "The effect of measurement error on the estimated shape of the world distribution of income," Economics Letters, Elsevier, vol. 100(3), pages 373-376, September.
- Kato, Kengo & Sasaki, Yuya, 2018. "Uniform confidence bands in deconvolution with unknown error distribution," Journal of Econometrics, Elsevier, vol. 207(1), pages 129-161.
- Max Köhler & Anja Schindler & Stefan Sperlich, 2014.
"A Review and Comparison of Bandwidth Selection Methods for Kernel Regression,"
International Statistical Review, International Statistical Institute, vol. 82(2), pages 243-274, August.
- Max Köhler & Anja Schindler & Stefan Sperlich, 2011. "A Review and Comparison of Bandwidth Selection Methods for Kernel Regression," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 95, Courant Research Centre PEG.
- BOUEZMARNI, Taoufik & ROMBOUTS, Jeroen V.K., 2007.
"Nonparametric density estimation for multivariate bounded data,"
LIDAM Discussion Papers CORE
2007065, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2007. "Nonparametric density estimation for multivariate bounded data," Cahiers de recherche 07-10, HEC Montréal, Institut d'économie appliquée.
- Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2007. "Nonparametric Density Estimation for Multivariate Bounded Data," Cahiers de recherche 0732, CIRPEE.
- Salim Bouzebda & Yousri Slaoui, 2023. "Nonparametric Recursive Estimation for Multivariate Derivative Functions by Stochastic Approximation Method," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 658-690, February.
- Peter Hall & Tapabrata Maiti, 2008. "Non‐parametric inference for clustered binary and count data when only summary information is available," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 725-738, September.
- Estévez-Pérez, Graciela, 2002. "On convergence rates for quadratic errors in kernel hazard estimation," Statistics & Probability Letters, Elsevier, vol. 57(3), pages 231-241, April.
- J. Vilar, 1995. "Kernel estimation of the regression function with random sampling times," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 4(1), pages 137-178, June.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2023.
"Bandwidth selection for nonparametric regression with errors-in-variables,"
Econometric Reviews, Taylor & Francis Journals, vol. 42(4), pages 393-419, April.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2021. "Bandwidth Selection for Nonparametric Regression with Errors-in-Variables," Departmental Working Papers 2104, Southern Methodist University, Department of Economics.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2022. "Bandwidth selection for nonparametric regression with errors-in-variables," STICERD - Econometrics Paper Series 620, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2023. "Bandwidth selection for nonparametric regression with errors-in-variables," LSE Research Online Documents on Economics 115551, London School of Economics and Political Science, LSE Library.
- Yousri Slaoui, 2021. "Data-driven Deconvolution Recursive Kernel Density Estimators Defined by Stochastic Approximation Method," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 312-352, February.
- Sun, Liuquan, 1997. "Bandwidth choice for hazard rate estimators from left truncated and right censored data," Statistics & Probability Letters, Elsevier, vol. 36(2), pages 101-114, December.
- Otsu, Taisuke & Taylor, Luke, 2021.
"Specification Testing For Errors-In-Variables Models,"
Econometric Theory, Cambridge University Press, vol. 37(4), pages 747-768, August.
- Taisuke Otsu & Luke Taylor, 2016. "Specification testing for errors-in-variables models," STICERD - Econometrics Paper Series /2015/586, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Otsu, Taisuke & Taylor, Luke, 2020. "Specification testing for errors-in-variables models," LSE Research Online Documents on Economics 102690, London School of Economics and Political Science, LSE Library.
- Wu, Colin O., 1997. "A Cross-Validation Bandwidth Choice for Kernel Density Estimates with Selection Biased Data," Journal of Multivariate Analysis, Elsevier, vol. 61(1), pages 38-60, April.
- Xiaodong Gong & Jiti Gao, 2015.
"Nonparametric Kernel Estimation of the Impact of Tax Policy on the Demand for Private Health Insurance in Australia,"
Monash Econometrics and Business Statistics Working Papers
6/15, Monash University, Department of Econometrics and Business Statistics.
- Xiaodong Gong & Jiti Gao, 2017. "Nonparametric kernel estimation of the impact of tax policy on the demand for private health insurance in Australia," Monash Econometrics and Business Statistics Working Papers 7/17, Monash University, Department of Econometrics and Business Statistics.
- Gong, Xiaodong & Gao, Jiti, 2015. "Nonparametric Kernel Estimation of the Impact of Tax Policy on the Demand for Private Health Insurance in Australia," IZA Discussion Papers 9265, Institute of Labor Economics (IZA).
More about this item
Keywords
Density estimation; Deconvolution; Cross-validation; Asymptotic optimality; 62F03; 62E17; 62P25;All these keywords.
JEL classification:
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:testjl:v:17:y:2008:i:1:p:138-162. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.