Generalization of the order-restricted information criterion for multivariate normal linear models

R M Kuiper, Herbert Hoijtink, Mervyn Joseph Silvapulle

Research output: Contribution to journalArticleResearchpeer-review

8 Citations (Scopus)

Abstract

The generalized order-restricted information criterion (goric) is a model selection criterion which can, up to now, solely be applied to the analysis of variance models and, so far, only evaluate restrictions of the form R theta <or = 0, where theta is a vector of k group means and R a cm x k matrix. In this paper, we generalize the goric in two ways: (i) such that it can be applied to t-variate normal linear models and (ii) such that it can evaluate a more general form of order restrictions: R theta <= r, where theta is a vector of length tk, r a vector of length cm, and R a cm x tk matrix of full rank (when r is not = 0). At the end, we illustrate that the goric is easy to implement in a multivariate regression model.
Original languageEnglish
Pages (from-to)2454 - 2463
Number of pages10
JournalJournal of Statistical Planning and Inference
Volume142
Issue number8
DOIs
Publication statusPublished - 2012

Cite this