Best feasible unbiased prediction for multi-source data system with an application for multiplicative benchmarking / Zhao-Guo Chen and Estela Bee Dagum. : CS11-617/98-9E-PDF
"Information about a socio-economic variable of interest (usually, one or a group of time series) often originates from several sources none of which is complete and/or accurate. A stepwise approach is developed here for predicting the variable of interest by using the data from source to source focusing on minimizing the variances of prediction errors. This paper also reviews some BLUP (the best linear unbiased prediction) theory and shows that the stepwise approach proposed here can give better predictions than BLUP for nonlinear models. As an important application, a nonlinear benchmarking formula for a multiplicative model is derived"--Summary.
Lien permanent pour cette publication :
publications.gc.ca/pub?id=9.840289&sl=1
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| Titre | Best feasible unbiased prediction for multi-source data system with an application for multiplicative benchmarking / Zhao-Guo Chen and Estela Bee Dagum. |
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| Type de publication | Monographie - Voir l'enregistrement principal |
| Langue | [Anglais] |
| Format | Texte numérique |
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| Description | 23 p. |
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| Numéro de catalogue du ministère | 11-617 no. 98-09 |
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