TY - JOUR
T1 - Bayesian local influence for the growth curve model with Rao's simple covariance structure
AU - Pan, Jian Xin
AU - Fang, Kai Tai
AU - Liski, Erkki P.
N1 - Funding Information:
This research was partially supported by the Hong Kong UGC Grant, the Academy of Finland, and the University of Tampere.
PY - 1996/7
Y1 - 1996/7
N2 - In this paper, the Bayesian local influence approach is employed to diagnose the adequacy of the growth curve model with Rao's simple covariance structure, based on the Kullback-Leibler divergence. The Bayesian Hessian matrices of the model are investigated in detail under an abstract perturbation scheme. For illustration, covariance-weighted perturbation is considered particularly and used to analyze two real-life biological data sets, which shows that the criteria presented in this article are useful in practice.
AB - In this paper, the Bayesian local influence approach is employed to diagnose the adequacy of the growth curve model with Rao's simple covariance structure, based on the Kullback-Leibler divergence. The Bayesian Hessian matrices of the model are investigated in detail under an abstract perturbation scheme. For illustration, covariance-weighted perturbation is considered particularly and used to analyze two real-life biological data sets, which shows that the criteria presented in this article are useful in practice.
KW - Bayesian hessian matrix
KW - Bayesian local influence
KW - Covariance weighted perturbation
KW - Growth curve model
KW - Kullback-Leibler divergence
KW - Statistical diagnostics
UR - http://www.scopus.com/inward/record.url?scp=0030187399&partnerID=8YFLogxK
U2 - 10.1006/jmva.1996.0039
DO - 10.1006/jmva.1996.0039
M3 - Journal article
AN - SCOPUS:0030187399
SN - 0047-259X
VL - 58
SP - 55
EP - 81
JO - Journal of Multivariate Analysis
JF - Journal of Multivariate Analysis
IS - 1
ER -