A unifying framework for $k$-statistics, polykays and their multivariate generalizations

Elvira Di Nardo; Giuseppe Guarino; Domenico Senato

doi:10.3150/07-BEJ6163

A unifying framework for $k$-statistics, polykays and their multivariate generalizations

组合数学 2008-05-19 v3 统计理论统计理论

作者: Elvira Di Nardo , Giuseppe Guarino , Domenico Senato

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摘要

Through the classical umbral calculus, we provide a unifying syntax for single and multivariate $k$ -statistics, polykays and multivariate polykays. From a combinatorial point of view, we revisit the theory as exposed by Stuart and Ord, taking into account the Doubilet approach to symmetric functions. Moreover, by using exponential polynomials rather than set partitions, we provide a new formula for $k$ -statistics that results in a very fast algorithm to generate such estimators.

关键词

kazhdan-lusztig polynomials

引用

@article{arxiv.math/0607623,
  title  = {A unifying framework for $k$-statistics, polykays and their multivariate generalizations},
  author = {Elvira Di Nardo and Giuseppe Guarino and Domenico Senato},
  journal= {arXiv preprint arXiv:math/0607623},
  year   = {2008}
}

备注

Published in at http://dx.doi.org/10.3150/07-BEJ6163 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)

A unifying framework for $k$-statistics, polykays and their multivariate generalizations

摘要

关键词

引用

备注

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