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2016
ACM

Fabular: regression formulas as probabilistic programming

10 months 26 days ago
Fabular: regression formulas as probabilistic programming
Regression formulas are a domain-specific language adopted by several R packages for describing an important and useful class of statistical models: hierarchical linear regressions. Formulas are succinct, expressive, and clearly popular, so are they a useful addition to probabilistic programming languages? And what do they mean? We propose a core calculus of hierarchical linear regression, in which regression coefficients are themselves defined by nested regressions (unlike in R). We explain how our calculus captures the essence of the formula DSL found in R. We describe the design and implementation of Fabular, a version of the Tabular schema-driven probabilistic programming language, enriched with formulas based on our regression calculus. To the best of our knowledge, this is the first formal description of the core ideas of R’s formula notation, the first development of a calculus of regression formulas, and the first demonstration of the benefits of composing regression ...
Johannes Borgström, Andrew D. Gordon, Long Ou
Added 09 Apr 2016
Updated 09 Apr 2016
Type Journal
Year 2016
Where POPL
Authors Johannes Borgström, Andrew D. Gordon, Long Ouyang, Claudio V. Russo, Adam Scibior, Marcin Szymczak
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