Variance estimation for semiparametric regression models by local averaging
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DOI: 10.1007/s11749-017-0553-3
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References listed on IDEAS
- Cai, T. Tony & Levine, Michael & Wang, Lie, 2009. "Variance function estimation in multivariate nonparametric regression with fixed design," Journal of Multivariate Analysis, Elsevier, vol. 100(1), pages 126-136, January.
- Fan, Jianqing & Peng, Heng & Huang, Tao, 2005. "Semilinear High-Dimensional Model for Normalization of Microarray Data: A Theoretical Analysis and Partial Consistency," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 781-796, September.
- Jianqing Fan & Shaojun Guo & Ning Hao, 2012. "Variance estimation using refitted cross‐validation in ultrahigh dimensional regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 74(1), pages 37-65, January.
- Tiejun Tong & Yuedong Wang, 2005. "Estimating residual variance in nonparametric regression using least squares," Biometrika, Biometrika Trust, vol. 92(4), pages 821-830, December.
- Fan, Jianqing & Yao, Qiwei, 1998. "Efficient estimation of conditional variance functions in stochastic regression," LSE Research Online Documents on Economics 6635, London School of Economics and Political Science, LSE Library.
- Zhang, Wenyang & Lee, Sik-Yum, 2000. "Variable Bandwidth Selection in Varying-Coefficient Models," Journal of Multivariate Analysis, Elsevier, vol. 74(1), pages 116-134, July.
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Cited by:
- Peng, Heng & Xie, Chuanlong & Zhao, Jingxin, 2021. "Fast inference for semi-varying coefficient models via local averaging," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
- Jun Zhang & Bingqing Lin & Yan Zhou, 2024. "Linear regression models with multiplicative distortions under new identifiability conditions," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 78(1), pages 25-67, February.
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Keywords
Variance estimation; Local averaging; Partial consistency; Semiparametric model;All these keywords.
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