Peanut/DESCRIPTION at master · ralmond/Peanut · GitHub

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Package: Peanut
Version: 0.9-3
Date: 2023/08/20
Title: Parameterized Bayesian Networks, Abstract Classes
Author: Russell Almond
Maintainer: Russell Almond <ralmond@fsu.edu>
Authors@R:
    person(given = "Russell",
           family = "Almond",
           role = c("aut", "cre"),
           email = "ralmond@fsu.edu",
           comment = c(ORCID = "0000-0002-8876-9337"))
Depends: R (>= 3.0), CPTtools (>= 0.5), methods
Imports: utils, futile.logger, jsonlite
Suggests:  PNetica,
    knitr,
    rmarkdown,
    tidyr,
    htmltools,
    shiny,
    shinyjs
VignetteBuilder: knitr
Description: This provides support of learning conditional probability
    tables parameterized using CPTtools. This provides and object oriented
    layer on top of a CPTtools, to facilitate calculations with
    Parameterized models for Bayesian networks.  Peanut is a collection of
    abstract classes and generic functions defining a protocol, with the
    intent that the protocol can be implemented  with different Bayes net
    engines.  The companion pacakge PNetica provides an implementation
    using Netica and RNetica.
License: Artistic-2.0
URL: http://pluto.coe.fsu.edu/RNetica
Support: c(
   'Bill & Melinda Gates Foundation grant
   "Games as Learning/Assessment:  Stealth Assessment" (#0PP1035331,
   Val Shute, PI)',
   'National Science Foundation grant "DIP:
   Game-based Assessment and Support of STEM-related Competencies"
   (#1628937, Val Shute, PI)',
   'National Science Foundation grant "Mathematical Learning via
   Architectural Design and Modeling Using E-Rebuild." (\#1720533,
   Fengfeng Ke, PI)',
   'Institute of Educational Statistics Grant: "Exploring adaptive cognitive and affective learning support for next-generation STEM learning games." (#R305A170376-20, Val Shute and Russell Almond, PIs')