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Benjamin Goodrich

Associate Research Scholar; Lecturer in the Department of Political Science

CI-SUSTAIN: Stan for the Long Run

Stan is a software package that transforms scientific discovery by allowing scientists to quickly and easily explore, evaluate, and refine rich scientific hypotheses tailored to their particular research question and data collection mechanism. For computational reasons, analyses of data (big or otherwise) have tended to be simple and focused more on the difficulties of manipulating the data than on realistic scientific models.

Regina Dolgoarshinnykh

Associate Research Scientist in the Department of Statistics; Adjunct Assistant Professor of Statistics

Sloan Proposal for Stan

To support the development, maintenance, and dissemination of Stan, a probabilistic programming language that simplifies Bayesian modeling and data analysis.

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