Comparison of Bootstrap and Jackknife Methods of Re-sampling in Estimating Population Parameters

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dc.contributor.authorOyeyemi, G. M.
dc.date.accessioned2023-07-19T14:10:18Z
dc.date.available2023-07-19T14:10:18Z
dc.date.issued2008
dc.description.abstractRe-sampling methods have been found to be useful for several purposes such as model selection linear regression and estimation of sampling variances or standard errors and confidence intervals. ln estimating the population coefficient of variation and its standard error, two methods of re-sampling Bootstrap and Jackknife are compared in this paper. The Jackknife method is found to require relatively small sample size to attain consistency in its estimate while Bootstrap requires larges ample size. Bootstrap is also found to always underestimate the standard error of its estimates.en_US
dc.description.sponsorshipSelf-sponsoreden_US
dc.identifier.citationGlobal Journal of Mathematical Sciencesen_US
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/11581
dc.language.isoenen_US
dc.publisherPublished by Bachudo Sciences Co. Ltden_US
dc.relation.ispartofseries14;217 - 220
dc.subjectBootstrap, Coefficient of variation, Jackknife, Sample size, Parametricen_US
dc.titleComparison of Bootstrap and Jackknife Methods of Re-sampling in Estimating Population Parametersen_US
dc.typeArticleen_US

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