ArticleInformation and inference : a journal of the IMA2022
Generalized score matching for general domains.
Article in Information and inference : a journal of the IMA, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Score Matching for Differential Abundance Testing of Compositional High-Throughput Sequencing Data.Statistics in medicine · 2026Article
- Covariate-Adjusted Inference for Differential Analysis of High-Dimensional Networks.Sankhya. Series A. (2008) · 2022Article
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Authors and funding
3 authors.
Funding
Abstract
Estimation of density functions supported on general domains arises when the data are naturally restricted to a proper subset of the real space. This problem is complicated by typically intractable normalizing constants. Score matching provides a powerful tool for estimating densities with such intractable normalizing constants but as originally proposed is limited to densities on [Formula: see text] and [Formula: see text]. In this paper, we offer a natural generalization of score matching that accommodates densities supported on a very general class of domains. We apply the framework to truncated graphical and pairwise interaction models and provide theoretical guarantees for the resulting estimators. We also generalize a recently proposed method from bounded to unbounded domains and empirically demonstrate the advantages of our method.
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Registered trials
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