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
F. Bertrand, M. Maumy-Bertrand

TL;DR
This paper introduces an automated Maple worksheet for deriving second-order Edgeworth and Cornish-Fisher expansions, applicable to various bootstrap methods and statistics, with tools for validation, correction, and visualization.
Contribution
It provides a novel, automated Maple tool for deriving and validating higher-order asymptotic expansions and related quantities for statistical estimators.
Findings
Identified an error in a classical second-order Cornish-Fisher expansion.
Highlighted the impact of normalizing constants on expansions of the t-distribution.
Successfully applied the worksheet to complex MLE estimators for improved confidence intervals.
Abstract
We designed a completely automated Maple () 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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStatistical Methods and Bayesian Inference · Advanced Statistical Methods and Models · Statistical Methods and Inference
