Statistical inference for inverse problems
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- Hajo Holzmann & Leif Boysen, 2006. "Integrated Square Error Asymptotics for Supersmooth Deconvolution," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(4), pages 849-860, December.
- Politis, Dimitris N. & Romano, Joseph P., 1999. "Multivariate Density Estimation with General Flat-Top Kernels of Infinite Order," Journal of Multivariate Analysis, Elsevier, vol. 68(1), pages 1-25, January.
- Enno Mammen, "undated".
"Comparing nonparametric versus parametric regression fits,"
Statistic und Oekonometrie
9205, Humboldt Universitaet Berlin.
- Hardle, W. & Mammen, E., 1990. "Comparing nonparametric versus parametric regression fits," LIDAM Discussion Papers CORE 1990065, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Iain M. Johnstone & Gérard Kerkyacharian & Dominique Picard & Marc Raimondo, 2004. "Wavelet deconvolution in a periodic setting," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(3), pages 547-573, August.
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- Meister, Alexander, 2009. "On testing for local monotonicity in deconvolution problems," Statistics & Probability Letters, Elsevier, vol. 79(3), pages 312-319, February.
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