Programming With Models: Writing Statistical Algorithms for General Model Structures With NIMBLE

PDPerry de ValpineDTDaniel TurekCJChristopher J. PaciorekCAClifford Anderson-BergmanDTDuncan Temple Lang

University of California, Berkeley · University of California, Davis

Indexed inarxivcrossref

Abstract

We describe NIMBLE, a system for programming statistical algorithms for general model structures within R. NIMBLE is designed to meet three challenges: flexible model specification, a language for programming algorithms that can use different models, and a balance between high-level programmability and execution efficiency. For model specification, NIMBLE extends the BUGS language and creates model objects, which can manipulate variables, calculate log probability values, generate simulations, and query the relationships among variables. For algorithm programming, NIMBLE provides functions that operate with model objects using two stages of evaluation. The first stage allows specialization of a function to a…

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997
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Authors

6
  • PD
    Perry de ValpineCorresponding

    University of California, Berkeley

  • DT
    Daniel Turek

    University of California, Berkeley

  • CJ
    Christopher J. Paciorek

    University of California, Berkeley

  • CA
    Clifford Anderson-Bergman

    University of California, Berkeley

  • DT
    Duncan Temple Lang

    University of California, Davis

Topics & keywords

Keywords
  • Computation
  • Markov chain Monte Carlo
  • Programming paradigm
  • Monte Carlo method
  • Language model
  • Statistical model
  • Block (permutation group theory)
  • Computational statistics
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