Abstract
The Boot.EXPOS procedure is an algorithm that combines the use of exponential smoothing methods with the bootstrap methodology for obtaining forecasts. It starts with the selection of an exponential smoothing method and evolves to a bootstrapping design based on the residuals. The time series is reconstructed and forecasts are obtained. That procedure, now extended to “predict” missing values, is named NABoot.EXPOS.
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Acknowledgements
Research partially supported by DM/FCT/Ualg and National Funds through FCT—Fundação para a Ciência e a Tecnologia, project PEst-OE/MAT/UI0006/2011, and[4]PTDC/FEDER.
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Cordeiro, C., Neves, M.M. (2013). Predicting and Treating Missing Data with Boot.EXPOS. In: Lita da Silva, J., Caeiro, F., Natário, I., Braumann, C. (eds) Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications. Studies in Theoretical and Applied Statistics(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34904-1_13
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DOI: https://doi.org/10.1007/978-3-642-34904-1_13
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