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Bandwidth selection for a class of difference-based variance estimators in the nonparametric regression: A possible approach

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  • Levine, M.

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  • Levine, M., 2006. "Bandwidth selection for a class of difference-based variance estimators in the nonparametric regression: A possible approach," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3405-3431, August.
  • Handle: RePEc:eee:csdana:v:50:y:2006:i:12:p:3405-3431
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    References listed on IDEAS

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    1. Hardle, W. & Tsybakov, A., 1997. "Local polynomial estimators of the volatility function in nonparametric autoregression," Journal of Econometrics, Elsevier, vol. 81(1), pages 223-242, November.
    2. 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.
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    Cited by:

    1. Boente, Graciela & Ruiz, Marcelo & Zamar, Ruben H., 2010. "On a robust local estimator for the scale function in heteroscedastic nonparametric regression," Statistics & Probability Letters, Elsevier, vol. 80(15-16), pages 1185-1195, August.
    2. Chen Zhong & Lijian Yang, 2021. "Simultaneous confidence bands for comparing variance functions of two samples based on deterministic designs," Computational Statistics, Springer, vol. 36(2), pages 1197-1218, June.
    3. Li Cai & Lijian Yang, 2015. "A smooth simultaneous confidence band for conditional variance function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 632-655, September.
    4. Giordano, F. & Parrella, M.L., 2008. "Neural networks for bandwidth selection in local linear regression of time series," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2435-2450, January.
    5. Boente, Graciela & Ruiz, Marcelo & Zamar, Ruben H., 2012. "Bandwidth choice for robust nonparametric scale function estimation," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1594-1608.

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