Asymptotic Normality of Kernel-Type Deconvolution Estimators
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- Mynbaev, Kairat & Martins-Filho, Carlos, 2015.
"Consistency and asymptotic normality for a nonparametric prediction under measurement errors,"
Journal of Multivariate Analysis,
Elsevier, vol. 139(C), pages 166-188.
- Mynbaev, Kairat & Martins-Filho, Carlos, 2015. "Consistency and asymptotic normality for a nonparametric prediction under measurement errors," MPRA Paper 75845, University Library of Munich, Germany, revised 2014.
- Jakob SÃ¶hl & Mathias Trabs, 2012. "We estimate linear functionals in the classical deconvolution problem by kernel estimators," SFB 649 Discussion Papers SFB649DP2012-046, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- 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.
- 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.
- Yang Zu, 2015. "A Note on the Asymptotic Normality of the Kernel Deconvolution Density Estimator with Logarithmic Chi-Square Noise," Econometrics, MDPI, Open Access Journal, vol. 3(3), pages 1-16, July.
- 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.
- 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.
- Bissantz, Nicolai & Dümbgen, Lutz & Holzmann, Hajo & Munk, Axel, 2007. "Nonparametric confidence bands in deconvolution density estimation," Technical Reports 2007,03, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Mynbaev, Kairat, 2011. "Distributions escaping to infinity and the limiting power of the Cliff-Ord test for autocorrelation," MPRA Paper 44402, University Library of Munich, Germany, revised 18 Sep 2012.
- Martin L. Hazelton & Berwin A. Turlach, 2010. "Semiparametric Density Deconvolution," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(1), pages 91-108.
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