Statistical Applications of the Complex-Step Method of Numerical Differentiation.
The complex-step method of numerical differentiation is described. This procedure is used to derive a numerical approximation to the first derivative of a function while avoiding the round-off error that characterizes standard finite difference approximations. An extension of the method allows for...
| Publicado en: | American Statistician Vol. 63; no. 1; pp. 66 - 75 |
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| Formato: | Artículo |
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American Statistical Association
February 2009
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=508041381&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 508041381 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00031305 STT jtl: American Statistician issn: 00031305 maglogo: N pubinfo: dt: February 2009 vid: 63 iid: 1 pid: 543 pub: American Statistical Association artinfo: ui: 508041381 10.1198/tast.2009.0013 ppf: 66 ppct: 9 formats: tig: atl: Statistical Applications of the Complex-Step Method of Numerical Differentiation. aug: au: Ridout, Martin S. su: Numerical analysis sug: subj: Numerical analysis ab: The complex-step method of numerical differentiation is described. This procedure is used to derive a numerical approximation to the first derivative of a function while avoiding the round-off error that characterizes standard finite difference approximations. An extension of the method allows for the calculation of second derivatives with less round-off error. The practical implementation of the method is discussed, with specific reference to R, and its effectiveness is considered in several statistical examples. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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