9 citations · 15 across the 9 of their papers we have counts for
6 papers · 1 filter
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…
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…
Nonparametric Clustering of Mixed Data Using Modified Chi-square Tests
Yawen Xu, Xin Gao, Xiaogang Wang
We propose a non-parametric method to cluster mixed data containing both continuous and discrete random variables. The product space of continuous and categorical sample spaces is…
Tuning parameter selection for penalized likelihood estimation of inverse covariance matrix
Xin Gao, Daniel Q. Pu, Yuehua Wu +1
In a Gaussian graphical model, the conditional independence between two variables are characterized by the corresponding zero entries in the inverse covariance matrix. Maximum like…