Non‐parametric confidence bands in deconvolution density estimation
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Abstract
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DOI: 10.1111/j.1467-9868.2007.599.x
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Citations
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Cited by:
- 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.
- 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.
- repec:jss:jstsof:39:i10 is not listed on IDEAS
- Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2021.
"Average Derivative Estimation Under Measurement Error,"
Econometric Theory, Cambridge University Press, vol. 37(5), pages 1004-1033, October.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2019. "Average Derivative Estimation Under Measurement Error," Departmental Working Papers 1901, Southern Methodist University, Department of Economics.
- Hao Dong & Taisuke Otsu & Luke Taylor, 2019. "Average derivative estimation under measurement error," STICERD - Econometrics Paper Series 602, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Dong, Hao & Otsu, Taisuke & Taylor, Luke, 2020. "Average derivative estimation under measurement error," LSE Research Online Documents on Economics 106489, London School of Economics and Political Science, LSE Library.
- Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers CWP37/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Kato, Kengo & Sasaki, Yuya, 2019. "Uniform confidence bands for nonparametric errors-in-variables regression," Journal of Econometrics, Elsevier, vol. 213(2), pages 516-555.
- Dong, Hao & Taylor, Luke, 2022.
"Nonparametric Significance Testing In Measurement Error Models,"
Econometric Theory, Cambridge University Press, vol. 38(3), pages 454-496, June.
- Hao Dong & Luke Taylor, 2020. "Nonparametric Significance Testing in Measurement Error Models," Departmental Working Papers 2003, Southern Methodist University, Department of Economics.
- Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers 37/13, Institute for Fiscal Studies.
- Hao Dong & Yuya Sasaki, 2022.
"Estimation of average derivatives of latent regressors: with an application to inference on buffer-stock saving,"
Departmental Working Papers
2204, Southern Methodist University, Department of Economics.
- Hao Dong & Yuya Sasaki, 2022. "Estimation of Average Derivatives of Latent Regressors: With an Application to Inference on Buffer-Stock Saving," Papers 2209.05914, arXiv.org.
- Ma, Jun & Marmer, Vadim & Yu, Zhengfei, 2023.
"Inference on individual treatment effects in nonseparable triangular models,"
Journal of Econometrics, Elsevier, vol. 235(2), pages 2096-2124.
- Jun Ma & Vadim Marmer & Zhengfei Yu, 2021. "Inference on Individual Treatment Effects in Nonseparable Triangular Models," Papers 2107.05559, arXiv.org, revised Feb 2023.
- Kato, Kengo & Kurisu, Daisuke, 2020. "Bootstrap confidence bands for spectral estimation of Lévy densities under high-frequency observations," Stochastic Processes and their Applications, Elsevier, vol. 130(3), pages 1159-1205.
- Kato, Kengo & Sasaki, Yuya, 2018. "Uniform confidence bands in deconvolution with unknown error distribution," Journal of Econometrics, Elsevier, vol. 207(1), pages 129-161.
- Birke, Melanie & Bissantz, Nicolai & Holzmann, Hajo, 2008. "Confidence bands for inverse regression models with application to gel electrophoresis," Technical Reports 2008,16, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
- Kurisu, Daisuke & Otsu, Taisuke, 2022. "On linearization of nonparametric deconvolution estimators for repeated measurements model," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
- van Es, Bert & Gugushvili, Shota, 2008. "Weak convergence of the supremum distance for supersmooth kernel deconvolution," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2932-2938, December.
- 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.
- 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.
- 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).
- 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.
- Birke, Melanie & Bissantz, Nicolai, 2007. "Shape constrained estimators in inverse regression models with convolution-type operator," Technical Reports 2007,35, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Wang, Xiao-Feng & Fan, Zhaozhi & Wang, Bin, 2010. "Estimating smooth distribution function in the presence of heteroscedastic measurement errors," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 25-36, January.
- Kurisu, Daisuke & Otsu, Taisuke, 2022. "On linearization of nonparametric deconvolution estimators for repeated measurements model," LSE Research Online Documents on Economics 112676, London School of Economics and Political Science, LSE Library.
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