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Symbolic computation of moments of sampling distributions

Author

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  • Di Nardo, E.
  • Guarino, G.
  • Senato, D.
Abstract
By means of the notion of umbrae indexed by multisets, a general method to express estimators and their products in terms of power sums is derived. A connection between the notion of multiset and integer partition leads immediately to a way to speed up procedures. Comparisons of computational times with known procedures show how this approach turns out to be more efficient in eliminating much unnecessary computation.

Suggested Citation

  • Di Nardo, E. & Guarino, G. & Senato, D., 2008. "Symbolic computation of moments of sampling distributions," Computational Statistics & Data Analysis, Elsevier, vol. 52(11), pages 4909-4922, July.
    • Handle: RePEc:eee:csdana:v:52:y:2008:i:11:p:4909-4922
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    References listed on IDEAS

    as
    1. Bellhouse, David R. & Philips, Robert & Stafford, James E., 1997. "Symbolic operators for multiple sums," Computational Statistics & Data Analysis, Elsevier, vol. 24(4), pages 443-454, June.
    2. Delicado, P. & Goria, M.N., 2008. "A small sample comparison of maximum likelihood, moments and L-moments methods for the asymmetric exponential power distribution," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1661-1673, January.
    3. Karvanen, Juha, 2006. "Estimation of quantile mixtures via L-moments and trimmed L-moments," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 947-959, November.
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    Cited by:

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    2. Christopher S. Withers & Saralees Nadarajah & Shou Hsing Shih, 2015. "Moments and Cumulants of a Mixture," Methodology and Computing in Applied Probability, Springer, vol. 17(3), pages 541-564, September.

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