Properties of BLUEs and BLUPs in Full vs. Small Linear Models with New Observations

Stephen J. Haslett, Augustyn Markiewicz, Simo Puntanen

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review


In this article we consider the partitioned linear model M12={y,X1β1+X2β2,V}, where μ = X1β1 + X2β2, and the corresponding small model M1={y,X1β1,V}, where μ1 = X1β1. These models are supplemented with the new unobservable random vector y∗, coming from y∗ = Kβ1 + ε∗, where the covariance matrix of y∗ is known as well as the cross-covariance matrix between y∗ and y. We focus on comparing the BLUEs of μ1 and μ, and BLUPs of y∗ and ε∗ under M12 and M1.
Original languageEnglish
Title of host publicationRecent Developments in Multivariate and Random Matrix Analysis
Subtitle of host publicationFestschrift in Honour of Dietrich von Rosen
EditorsThomas Holgersson, Martin Singull
Number of pages24
ISBN (Electronic)978-3-030-56773-6
ISBN (Print)978-3-030-56772-9
Publication statusPublished - 2020
Publication typeA3 Part of a book or another research book

Publication forum classification

  • Publication forum level 2


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