Inference of Multiscale Gaussian Graphical Model. (arXiv:2202.05775v2 [stat.ML] UPDATED)

Web: http://arxiv.org/abs/2202.05775

Gaussian Graphical Models (GGMs) are widely used for exploratory data
analysis in various fields such as genomics, ecology, psychometry. In a
high-dimensional setting, when the number of variables exceeds the number of
observations by several orders of magnitude, the estimation of GGM is a
difficult and unstable optimization problem. Clustering of variables or
variable selection is often performed prior to GGM estimation. We propose a new
method allowing to simultaneously infer a hierarchical clustering structure and
the graphs describing the …

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