Efficient estimation of the error distribution function in heteroskedastic nonparametric regression with missing data
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DOI: 10.1016/j.spl.2016.04.009
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References listed on IDEAS
- Müller, Ursula U. & Schick, Anton & Wefelmeyer, Wolfgang, 2009. "Estimating the error distribution function in nonparametric regression with multivariate covariates," Statistics & Probability Letters, Elsevier, vol. 79(7), pages 957-964, April.
- Neumeyer, N. & Van Keilegom, I., 2010. "Estimating the error distribution in nonparametric multiple regression with applications to model testing," LIDAM Reprints ISBA 2010006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Neumeyer, Natalie & Van Keilegom, Ingrid, 2010. "Estimating the error distribution in nonparametric multiple regression with applications to model testing," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1067-1078, May.
- Justin Chown & Ursula U. Müller, 2013. "Efficiently estimating the error distribution in nonparametric regression with responses missing at random," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(3), pages 665-677, September.
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Cited by:
- Xu, Hong-Xia & Fan, Guo-Liang & Chen, Zhen-Long, 2017. "Hypothesis tests in partial linear errors-in-variables models with missing response," Statistics & Probability Letters, Elsevier, vol. 126(C), pages 219-229.
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Keywords
Heteroskedastic; Nonparametric regression; Local polynomial smoother; Transfer principle; Efficient estimator; Empirical distribution function;All these keywords.
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