David Prince
Various methods, with corresponding assumptions, exist for estimating graphical models in the multivariate Gaussian case. Two such methods are the LASSO and the adaptive LASSO which require the assumptions of neighborhood stability and restricted eigenvalue, respectively. In this talk, I present the methods and results of a simulation study assessing the validity of the assumptions using three different network generation models (Erdos-Renyi random graph, Watts-Strogatz rewired lattice and Barabasi-Albert preferential attachment network).
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