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.

A new method for fast computing unbiased estimators of cumulants

DI NARDO, Elvira;
2009-01-01

Abstract

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.
2009
19
2
155
165
http://www.springerlink.com/content/q660238j975432km/
Univariate and multivariate k-statistics - Univariate and multivariate polykays - Umbral calculus
E. DI NARDO; G. GUARINO; D. SENATO PULLANO
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1561325
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