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Variable selection in neural network regression models with dependent data: a subsampling approach

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  • La Rocca, Michele
  • Perna, Cira

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  • La Rocca, Michele & Perna, Cira, 2005. "Variable selection in neural network regression models with dependent data: a subsampling approach," Computational Statistics & Data Analysis, Elsevier, vol. 48(2), pages 415-429, February.
    • Handle: RePEc:eee:csdana:v:48:y:2005:i:2:p:415-429
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    References listed on IDEAS

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    1. Hardle, W. & Vieu, P., 1990. "Kernel regression smoothing of time series," LIDAM Discussion Papers CORE 1990031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    Cited by:

    1. Giordano, Francesco & Parrella, Maria Lucia, 2016. "Bias-corrected inference for multivariate nonparametric regression: Model selection and oracle property," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 71-93.
    2. Francesco Giordano & Maria Lucia Parrella, 2014. "Bias-corrected inference for multivariate nonparametric regression: model selection and oracle property," Working Papers 3_232, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.
    3. Dalibor Petković & Milan Gocic & Slavisa Trajkovic & Miloš Milovančević & Dragoljub Šević, 2017. "Precipitation concentration index management by adaptive neuro-fuzzy methodology," Climatic Change, Springer, vol. 141(4), pages 655-669, April.
    4. Michele La Rocca & Cira Perna, 2022. "Opening the Black Box: Bootstrapping Sensitivity Measures in Neural Networks for Interpretable Machine Learning," Stats, MDPI, vol. 5(2), pages 1-18, April.
    5. Giordano, Francesco & La Rocca, Michele & Perna, Cira, 2007. "Forecasting nonlinear time series with neural network sieve bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3871-3884, May.
    6. Steven M. Ramsey & Jason S. Bergtold, 2021. "Examining Inferences from Neural Network Estimators of Binary Choice Processes: Marginal Effects, and Willingness-to-Pay," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1137-1165, December.
    7. Wu, Edmond H.C. & Yu, Philip L.H. & Li, W.K., 2009. "A smoothed bootstrap test for independence based on mutual information," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2524-2536, May.

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