JACKKNIFING THE GENERAL LINEAR MODEL

dc.contributor.authorWeber, N. C.en
dc.contributor.authorWelsh, A. H.en
dc.date.accessioned2026-01-01T10:41:42Z
dc.date.available2026-01-01T10:41:42Z
dc.date.issued1983en
dc.description.abstractThe aim of this paper is to investigate the problems of estimating a smooth function of the parameters in a general linear model and to clarify some of the points raised by Hinkley (1977) in connection with this problem. An example of the type of problem at hand is that of estimating the maximum (or minimum) mean value in a quadratic regression model. The estimator based on the least squares estimator of the parameters in the linear model is compared to the jackknife estimator and the weighted jackknife estimator proposed by Hinkley (1977). The asymptotic properties of the estimators are examined and their small sample properties are compared through simulation studies.en
dc.description.statusPeer-revieweden
dc.format.extent12en
dc.identifier.issn0004-9581en
dc.identifier.scopus84985521997en
dc.identifier.urihttps://hdl.handle.net/1885/733799776
dc.language.isoenen
dc.sourceAustralian Journal of Statisticsen
dc.titleJACKKNIFING THE GENERAL LINEAR MODELen
dc.typeJournal articleen
dspace.entity.typePublicationen
local.bibliographicCitation.lastpage436en
local.bibliographicCitation.startpage425en
local.contributor.affiliationWeber, N. C.; Department of Mathematical Statisticsen
local.contributor.affiliationWelsh, A. H.; Department of Mathematical Statisticsen
local.identifier.citationvolume25en
local.identifier.doi10.1111/j.1467-842X.1983.tb01213.xen
local.identifier.pure5395842a-a89c-40ee-bf44-ad876417d91aen
local.identifier.urlhttps://www.scopus.com/pages/publications/84985521997en
local.type.statusPublisheden

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