[HTML][HTML] Sparse covariance estimation in heterogeneous samples
A Rodriguez, A Lenkoski, A Dobra - Electronic journal of statistics, 2011 - ncbi.nlm.nih.gov
Standard Gaussian graphical models implicitly assume that the conditional independence
among variables is common to all observations in the sample. However, in practice,
observations are usually collected from heterogeneous populations where such an
assumption is not satisfied, leading in turn to nonlinear relationships among variables. To
address such situations we explore mixtures of Gaussian graphical models; in particular, we
consider both infinite mixtures and infinite hidden Markov models where the emission …
among variables is common to all observations in the sample. However, in practice,
observations are usually collected from heterogeneous populations where such an
assumption is not satisfied, leading in turn to nonlinear relationships among variables. To
address such situations we explore mixtures of Gaussian graphical models; in particular, we
consider both infinite mixtures and infinite hidden Markov models where the emission …
[PDF][PDF] Sparse covariance estimation in heterogeneous samples
A Rodrıguez, A Lenkoski, A Dobra - Electron. J. Stat, 2011 - sites.stat.washington.edu
Standard Gaussian graphical models implicitly assume that the conditional independence
among variables is common to all observations in the sample. However, in practice,
observations are usually collected from heterogeneous populations where such an
assumption is not satisfied, leading in turn to nonlinear relationships among variables. To
address such situations we explore mixtures of Gaussian graphical models; in particular, we
consider both infinite mixtures and infinite hidden Markov models where the emission …
among variables is common to all observations in the sample. However, in practice,
observations are usually collected from heterogeneous populations where such an
assumption is not satisfied, leading in turn to nonlinear relationships among variables. To
address such situations we explore mixtures of Gaussian graphical models; in particular, we
consider both infinite mixtures and infinite hidden Markov models where the emission …