A Note on the Lasso for Gaussian Graphical Model Selection
نویسنده
چکیده
Inspired by the success of the Lasso for regression analysis (Tibshirani, 1996), it seems attractive to estimate the graph of a multivariate normal distribution by `1-norm penalised likelihood maximisation. The objective function is convex and the graph estimator can thus be computed efficiently, even for very large graphs. However, we show in this note that the resulting estimator is not consistent for some graphs.
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