Bootstrap bandwidth selection in kernel density estimation from a contaminated sample
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DOI: 10.1007/BF02530523
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References listed on IDEAS
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Cited by:
- Hao Dong & Taisuke Otsu & Luke Taylor, 2023.
"Bandwidth selection for nonparametric regression with errors-in-variables,"
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- 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.
- 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.
- 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.
- Xian, Yujiao & Yu, Dan & Wang, Ke & Yu, Jian & Huang, Zhimin, 2022. "Capturing the least costly measure of CO2 emission abatement: Evidence from the iron and steel industry in China," Energy Economics, Elsevier, vol. 106(C).
- Wang, B. & Wertelecki, W., 2013. "Density estimation for data with rounding errors," Computational Statistics & Data Analysis, Elsevier, vol. 65(C), pages 4-12.
- Julie McIntyre & Brent A. Johnson & Stephen M. Rappaport, 2018. "Monte Carlo methods for nonparametric regression with heteroscedastic measurement error," Biometrics, The International Biometric Society, vol. 74(2), pages 498-505, June.
- Julie McIntyre & Leonard Stefanski, 2011. "Density Estimation with Replicate Heteroscedastic Measurements," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(1), pages 81-99, February.
- Fabienne Comte & Adeline Samson & Julien J Stirnemann, 2014. "Deconvolution Estimation of Onset of Pregnancy with Replicate Observations," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 325-345, June.
- Delaigle, A. & Gijbels, I., 2006. "Data-driven boundary estimation in deconvolution problems," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 1965-1994, April.
- Fabienne Comte & Adeline Samson, 2012. "Nonparametric estimation of random-effects densities in linear mixed-effects model," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(4), pages 951-975, December.
- 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).
- 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.
- 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.
- William Horrace & Christopher Parmeter, 2011.
"Semiparametric deconvolution with unknown error variance,"
Journal of Productivity Analysis, Springer, vol. 35(2), pages 129-141, April.
- William C. Horrace & Christopher F. Parmeter, 2008. "Semiparametric Deconvolution with Unknown Error Variance," Center for Policy Research Working Papers 104, Center for Policy Research, Maxwell School, Syracuse University.
- 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.
- Gwennaëlle Mabon, 2014. "Adaptive Estimation of Random-Effects Densities In Linear Mixed-Effects Model," Working Papers 2014-41, Center for Research in Economics and Statistics.
- Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2022.
"Estimation of varying coefficient models with measurement error,"
Journal of Econometrics, Elsevier, vol. 230(2), pages 388-415.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2019. "Estimation of Varying Coefficient Models with Measurement Error," Departmental Working Papers 1905, Southern Methodist University, Department of Economics.
- Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2022. "Estimation of varying coefficient models with measurement error," LSE Research Online Documents on Economics 108147, London School of Economics and Political Science, LSE Library.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2019. "Estimation of Varying Coefficient Models with Measurement Error," STICERD - Econometrics Paper Series 607, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Adriano Z. Zambom & Ronaldo Dias, 2013. "A Review of Kernel Density Estimation with Applications to Econometrics," International Econometric Review (IER), Econometric Research Association, vol. 5(1), pages 20-42, April.
- Adusumilli, Karun & Kurisu, Daisuke & Otsu, Taisuke & Whang, Yoon-Jae, 2020.
"Inference on distribution functions under measurement error,"
Journal of Econometrics, Elsevier, vol. 215(1), pages 131-164.
- Karun Adusumilli & Taisuke Otsu & Yoon-Jae Whang, "undated". "Inference On Distribution Functions Under Measurement Error," Working Paper Series no108, Institute of Economic Research, Seoul National University.
- Adusumilli, Karun & Kurisu, Daisies & Otsu, Taisuke & Whang, Yoon-Jae, 2020. "Inference on distribution functions under measurement error," LSE Research Online Documents on Economics 102692, London School of Economics and Political Science, LSE Library.
- Karun Adusumilli & Taisuke Otsu & Yoon-Jae Whang, 2017. "Inference on distribution functions under measurement error," STICERD - Econometrics Paper Series 594, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Hao Dong & Daniel L. Millimet, 2020.
"Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions,"
JRFM, MDPI, vol. 13(11), pages 1-24, November.
- Dong, Hao & Millimet, Daniel L., 2020. "Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions," IZA Discussion Papers 13893, Institute of Labor Economics (IZA).
- Hao Dong & Daniel L. Millimet, 2020. "Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions," Departmental Working Papers 2013, Southern Methodist University, Department of Economics.
- 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.
- Delaigle, Aurore & Hall, Peter, 2006. "On optimal kernel choice for deconvolution," Statistics & Probability Letters, Elsevier, vol. 76(15), pages 1594-1602, September.
- Fabienne Comte & Gwennaelle Mabon & Adeline Samson, 2017. "Spline regression for hazard rate estimation when data are censored and measured with error," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 71(2), pages 115-140, May.
- Gwennaëlle Mabon, 2017. "Adaptive Deconvolution on the Non-negative Real Line," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(3), pages 707-740, September.
- Johanna Kappus & Gwennaelle Mabon, 2013. "Adaptive Density Estimation in Deconvolution Problems with Unknown Error Distribution," Working Papers 2013-31, Center for Research in Economics and Statistics.
- Fabienne Comte & Adeline Samson & Julien J. Stirnemann, 2018. "Hazard estimation with censoring and measurement error: application to length of pregnancy," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 338-359, June.
- Gwennaëlle Mabon, 2014. "Adaptive Deconvolution on the Nonnegative Real Line," Working Papers 2014-40, Center for Research in Economics and Statistics.
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Keywords
Bandwidth selection; bootstrap; consistency; deconvolution; errors-in-variables; kernel density estimation;All these keywords.
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