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Computationally efficient double bootstrap variance estimation
Department of Economic Statistics, Stockholm School of Economics, Stockholm, Sweden. (Stat@oru)ORCID iD: 0000-0003-0203-4688
Department of Economic Statistics, Stockholm School of Economics, Stockholm, Sweden.
2000 (English)In: Computational Statistics & Data Analysis, ISSN 0167-9473, E-ISSN 1872-7352, Vol. 33, no 3, p. 237-247Article in journal (Refereed) Published
Abstract [en]

The double bootstrap provides a useful tool for bootstrapping approximately pivotal quantities by using an "inner" bootstrap loop to estimate the variance. When the estimators are computationally intensive, the double bootstrap may become infeasible. We propose the use of a new variance estimator for the nonparametric bootstrap which effectively removes the requirement to perform the inner loop of the double bootstrap. Simulation results indicate that the proposed estimator produce bootstrap-t confidence intervals with coverage accuracy which replicates the coverage accuracy for the standard double bootstrap.

Place, publisher, year, edition, pages
Elsevier, 2000. Vol. 33, no 3, p. 237-247
Keywords [en]
bootstrap-t; confidence intervals; influence function; nonparametric bootstrap
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:oru:diva-61131DOI: 10.1016/S0167-9473(99)00066-3ISI: 000087280600001Scopus ID: 2-s2.0-0343962985OAI: oai:DiVA.org:oru-61131DiVA, id: diva2:1144096
Available from: 2017-09-25 Created: 2017-09-25 Last updated: 2017-09-27Bibliographically approved

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Karlsson, Sune

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