On Bootstrapping Using Smoothed Bootstrap

  • Sulafah BinhimdEmail author
Conference paper


The standard bootstrap method was introduced as a resampling method for statistical inference; it is a computer based method for assigning measures of accuracy to statistical estimates. The bootstrap sample is obtained by randomly sampling n times, with replacement, from the original sample. Thereafter, different versions of bootstrap were developed such as smoothed bootstrap. The smoothed bootstrap method uses n observations to create n + 1 intervals, and then sample the observations from these intervals. This paper will discuss the smoothed bootstrap method and compare it to the standard method via simulation studies.


Bootstrap Smoothed bootstrap Prediction interval Resampling method 


  1. 1.
    Efron, B.: Bootstrap methods: another look at the jackknife. Ann. Stat. 7, 1–26 (1979). Scholar
  2. 2.
    Banks, D.L.: Histospline smoothing the Bayesian bootstrap. Biometrika 75, 673–684 (1988). Scholar
  3. 3.
    Efron, B., Tibshirani, R.J.: An Introduction to the Bootstrap. Chapman and Hall (1993)Google Scholar
  4. 4.
    Mojirsheibani, M.: Iterated bootstrap prediction intervals. Stat. Sin. 8, 489–504 (1998)MathSciNetzbMATHGoogle Scholar
  5. 5.
    Adakeye, K.S., Lamidi, M.A., Osanaiye, P.A.: Prediction interval: a tool for monitoring outbreak of some prominent diseases. Glob. J. Maths 2, 41–46 (2010)Google Scholar
  6. 6.
    Mojirsheibani, M., Tibshirani, R.: Some results on bootstrap prediction intervals. Can. J. Stat. 24, 549–568 (1996). Scholar
  7. 7.
    Goncalves, S., Perron, B., Djogbenou, A.: Bootstrap prediction intervals for factor models. J. Bus. Econ. Stat. 35, 53–69 (2017). Scholar
  8. 8.
    Errouissi, R., Cardenas-Berrera, J., Meng, J., Castillo-Guerra, E., Gong, X., Chang, L.: Bootstrap prediction interval estimation for wind speed forecasting. In: Energy Conversion Congress and Exposition (ECCE). IEEE (2015).
  9. 9.
    Lu, M.C., Chang, D.S.: Bootstrap prediction intervals for Birnbaum-Saunders distribution. Microelectron. Reliab. 37, 1213–1216 (1997)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Faculty of Science, Department of StatisticsKing Abdulaziz UniversityJeddahSaudi Arabia

Personalised recommendations