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Interaction Models and Generalized Score Matching for Compositional Data
Applications such as the analysis of microbiome data have led to renewed interest in statistical methods for compositional data, i. e., multivariate data in the form of probability vectors that contain relative proportions.
Generalized Score Matching for General Domains
Score matching provides a powerful tool for estimating densities with such intractable normalizing constants, but as originally proposed is limited to densities on $\mathbb{R}^m$ and $\mathbb{R}_+^m$.
Generalized Score Matching for Non-Negative Data
The score matching method of Hyv\"arinen [2005] avoids direct calculation of the normalizing constant and yields closed-form estimates for exponential families of continuous distributions over $\mathbb{R}^m$.
