Mostra el registre d'ítem simple
Fitting a linear regression model by combining least squares and least absolute value estimation
dc.contributor.author | Allende, Sira |
dc.contributor.author | Bouza, Carlos |
dc.contributor.author | Romero, Isidro |
dc.date.accessioned | 2007-12-07T10:21:46Z |
dc.date.available | 2007-12-07T10:21:46Z |
dc.date.issued | 1995 |
dc.identifier.citation | Allende, Sira; Bouza, Carlos; Romero, Isisdro. "Fitting a linear regression model by combining least squares and least absolute value estimation". Qüestiió. 1995, vol. 19, núm. 1-3 |
dc.identifier.issn | 0210-8054 (versió paper) |
dc.identifier.uri | http://hdl.handle.net/2099/4056 |
dc.description.abstract | Robust estimation of the multiple regression is modeled by using a convex combination of Least Squares and Least Absolute Value criterions. A Bicriterion Parametric algorithm is developed for computing the corresponding estimates. The proposed procedure should be specially useful when outliers are expected. Its behavior is analyzed using some examples. |
dc.format.extent | 16 p. |
dc.language.iso | eng |
dc.publisher | Institut d'Estadística de Catalunya |
dc.rights | Attribution-NonCommercial-NoDerivs 2.5 Spain |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/2.5/es/ |
dc.subject.lcsh | Inference |
dc.subject.other | Outliers in regression |
dc.subject.other | L1 regression |
dc.subject.other | Bicriterion parametric algorithm |
dc.title | Fitting a linear regression model by combining least squares and least absolute value estimation |
dc.type | Article |
dc.subject.lemac | Inferència |
dc.subject.ams | Classificació AMS::62 Statistics::62F Parametric inference |
dc.subject.ams | Classificació AMS::62 Statistics::62J Linear inference, regression |
dc.rights.access | Open Access |
local.ordre | 7 |
local.personalitzacitacio | true |