A new method for fast computing unbiased estimators of cumulants
We propose new algorithms for generating k -statistics, multivariate k -statistics, polykays and multivariate polykays. The resulting computational times are very fast compared with procedures existing in the literature. Such speeding up is obtained by means of a symbolic method arising from the cla...
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Veröffentlicht in: | Statistics and computing 2009-06, Vol.19 (2), p.155-165 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | We propose new algorithms for generating
k
-statistics, multivariate
k
-statistics, polykays and multivariate polykays. The resulting computational times are very fast compared with procedures existing in the literature. Such speeding up is obtained by means of a symbolic method arising from the classical umbral calculus. The classical umbral calculus is a light syntax that involves only elementary rules to managing sequences of numbers or polynomials. The cornerstone of the procedures here introduced is the connection between cumulants of a random variable and a suitable compound Poisson random variable. Such a connection holds also for multivariate random variables. |
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ISSN: | 0960-3174 1573-1375 |
DOI: | 10.1007/s11222-008-9080-0 |