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A Sheet of Maple to Compute Second-Order Edgeworth Expansions and Related Quantities of any Function of the Mean of an iid Sample of an Absolutely Continuous Distribution

2018/09/30 by F. Bertrand, Bertrand, F., M. Maumy-Bertrand +1
Mathematics · #62E20 #62F12 #62F25 #62F40 #62G09 #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Statistics Theory (math.ST) #math.ST #msc:62E20 #msc:62F12 #msc:62F25 #msc:62F40 #msc:62G09 #stat.CO #stat.TH

paper · pdf · doi:10.48550/arxiv.1810.00289

20 pages, 8 figures, code snippet

arxiv created 2018/09/30 · arxiv updated 2018/10/02

Abstract

We designed a completely automated Maple (\geqslant 15) worksheet for deriving Edgeworth and Cornish-Fisher expansions as well as the acceleration constant of the bootstrap bias-corrected and accelerated technique. It is valid for non-parametric or parametric bootstrap, of any (studentized) statistics that is -a regular enough- function of the mean of an iid sample of an absolutely continuous distribution. This worksheet allowed us to point out one error in the second-order Cornish-Fisher expansion of the studentized mean stated in Theorem 13.5 by Das Gupta in [8, p. 194] as well as lay the stress on the influence of the slight change of the normalizing constant when computing the second-order Edgeworth and Cornish-Fisher expansions of the t-distribution as stated in Theorem 11.4.2 by Lehman and Romano in [14, p. 460]. In addition, we successfully applied the worksheet to a complex maximum likelihood estimator as a first step to derive more accurate confidence intervals in order to enhance quality controls. The worksheet also features export of Maple results into R code. In addition, we provide R code to plot these expansions as well as their increasing rearrangements. All these supplemental materials are available upon request.

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