Service disruption

Due to maintenance, the website may operate intermittently between 5:00 am ET until 9:00 am ET on Sunday, October 22, 2017.

Best feasible unbiased prediction for multi-source data system with an application for multiplicative benchmarking: 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.

Permanent link to this Catalogue Record: What is a permanent link?
MARC XML Format   MARC HTML Format

Department/Agency Statistics Canada. Methodology Branch.
Title Best feasible unbiased prediction for multi-source data system with an application for multiplicative benchmarking
Series Title Working paper ;
Publication Type Series - View Master Record
Language [English]
Format Electronic
Electronic Document

Archived Content

Information identified as archived is provided for reference, research or recordkeeping purposes. It is not subject to the Government of Canada Web Standards and has not been altered or updated since it was archived. Please contact the authoring department to request a format other than those available.

We invite you to consult the Frequently Asked Questions page for additional information regarding the Archived Content notice.

Having trouble opening this document?

Note: The URLs contained in this/these document(s) may no longer be functional
Note Digitized edition from print [produced by Statistics Canada]. "Working paper No. BSMD-98-009E." "October 1998."
Date 1998.
Number of Pages 23 p.
Catalogue Number
  • CS11-617/98-9E-PDF
Departmental Catalogue Number 11-617 no. 98-09
Subject Terms Statistical analysis, Methodology