Package: Peanut Version: 0.9-3 Date: 2023/08/20 Title: Parameterized Bayesian Networks, Abstract Classes Author: Russell Almond Maintainer: Russell Almond 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') Config/pak/sysreqs: libicu-dev Repository: https://ralmond.r-universe.dev Date/Publication: 2026-01-27 22:17:27 UTC RemoteUrl: https://github.com/ralmond/Peanut RemoteRef: HEAD RemoteSha: e3f6ea606a2d2d3efdf7b7b762730938d4d9999a NeedsCompilation: no Packaged: 2026-07-03 16:11:08 UTC; root