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dc.contributor.authorFrey, Daniel
dc.date.accessioned2013-05-01T19:17:12Z
dc.date.available2013-05-01T19:17:12Z
dc.date.issued2011
dc.date.submitted2011-09
dc.identifier.isbn978-1-4577-0626-4
dc.identifier.urihttp://hdl.handle.net/1721.1/78662
dc.description.abstractThis paper concerns the problem of calculating expectation shift due to variability which tends to occur whenever the function of a random variable is nonlinear and especially tends to occur in the neighborhood of a local maximum or minimum. The paper presents five theorems suggesting sampling points and formulae for estimating mean shift covering some of the most common cases of practical interest including multivariate normal distributions and uniform distributions as well as more general theorems covering all symmetric multivariate probability density functions.en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICQR.2011.6031688en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike 3.0en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourceOther University Web Domainen_US
dc.titleCalculating Expectation Shiften_US
dc.title.alternativeEfficiently estimating mean shift due to variabilityen_US
dc.typeArticleen_US
dc.identifier.citationFrey, D. D. “Efficiently estimating mean shift due to variability.” Proceedings of the 2011 IEEE International Conference on Quality and Reliability (ICQR), 2011. 95–100.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.mitauthorFrey, Daniel
dc.relation.journalProceedings of the 2011 IEEE International Conference on Quality and Reliability (ICQR)en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
dspace.orderedauthorsFrey, D. D.en
dc.identifier.orcidhttps://orcid.org/0000-0002-9886-7512
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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