TY - JOUR

T1 - Generalization of the order-restricted information criterion for multivariate normal linear models

AU - Kuiper, R M

AU - Hoijtink, Herbert

AU - Silvapulle, Mervyn Joseph

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

U2 - 10.1016/j.jspi.2012.03.007

DO - 10.1016/j.jspi.2012.03.007

M3 - Article

VL - 142

SP - 2454

EP - 2463

JO - Journal of Statistical Planning and Inference

JF - Journal of Statistical Planning and Inference

SN - 0378-3758

IS - 8

ER -