9 citations · 15 across the 9 of their papers we have counts for
10 papers
Penalized composite likelihood for colored graphical Gaussian models
Qiong Li, Xiaoying Sun, Nanwei Wang
This paper proposes a penalized composite likelihood method for model selection in colored graphical Gaussian models. The method provides a sparse and symmetry-constrained estimato…
Bayesian model selection approach for colored graphical Gaussian models
Qiong Li, Xin Gao, Helene Massam
We consider a class of colored graphical Gaussian models obtained by placing symmetry constraints on the precision matrix in a Bayesian framework. The prior distribution on the pre…
Data Integration with High Dimensionality
Xin Gao, Raymond J. Carroll
We consider a problem of data integration. Consider determining which genes affect a disease. The genes, which we call predictor objects, can be measured in different experiments o…
Approximate Bayesian estimation in large coloured graphical Gaussian models
Qiong Li, Xin Gao, Helene Massam
Distributed estimation methods have recently been used to compute the maximum likelihood estimate of the precision matrix for large graphical Gaussian models. Our aim, in this pape…
Bayesian precision matrix estimation for graphical Gaussian models with edge and vertex symmetries
Helene Massam, Qiong Li, Xin Gao
Graphical Gaussian models with edge and vertex symmetries were introduced by \citet{HojLaur:2008} who also gave an algorithm to compute the maximum likelihood estimate of the preci…
Multiple Comparisons using Composite Likelihood in Clustered Data
Mahdis Azadbakhsh, Xin Gao, Hanna Jankowski
We study the problem of multiple hypothesis testing for multidimensional data when inter-correlations are present. The problem of multiple comparisons is common in many application…