Package: vibass 0.0.55

Facundo Muñoz

vibass: Valencia International Bayesian Summer School

Materials for the introductory course on Bayesian inference. Practicals, data and interactive apps.

Authors:VIBASS7 [aut], Facundo Muñoz [ctb, cre], Carmen Armero [ctb], Anabel Forte [ctb], David Conesa [ctb], Mark Brewer [ctb], Virgilio Gómez-Rubio [ctb]

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vibass.pdf |vibass.html✨
vibass/json (API)

# Install 'vibass' in R:
install.packages('vibass', repos = c('https://vabar.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/vabar/vibass/issues

Pkgdown site:https://vabar.es

Datasets:

On CRAN:

Conda:

bayesian-inferenceteaching

5.40 score 7 stars 2 scripts 3 exports 81 dependencies

Last updated 8 months agofrom:28af94ba1f. Checks:1 OK, 7 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 10 2025
R-4.5-winNOTEFeb 10 2025
R-4.5-macNOTEFeb 10 2025
R-4.5-linuxNOTEFeb 10 2025
R-4.4-winNOTEFeb 10 2025
R-4.4-macNOTEFeb 10 2025
R-4.3-winNOTEFeb 10 2025
R-4.3-macNOTEFeb 10 2025

Exports:available_appssummary_tablevibass_app

Dependencies:attemptbase64encBayesXsrcbootbslibcachemclicolorspacecommonmarkconfigcpp11crayondigestdplyrevaluateextraDistrfansifarverfastmapfontawesomefsgenericsggplot2gluegolemgtableherehighrhtmltoolshttpuvisobandjquerylibjsonliteknitrlabelinglaterlatticelifecyclelme4magrittrMASSMatrixmemoisemgcvmimeminqamunsellnlmenloptrpillarpkgconfigpromisespurrrR2BayesXR6rappdirsrbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangrprojrootrstudioapisassscalesshinysourcetoolsstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrxfunxtableyaml

Practical 1: Binary data

VIBASS

Rendered fromp1.Rmdusingknitr::rmarkdownon Feb 10 2025.

Last update: 2023-07-09
Started: 2021-05-31

Practical 2: Count data

VIBASS

Rendered fromp2count.Rmdusingknitr::rmarkdownon Feb 10 2025.

Last update: 2024-07-08
Started: 2023-07-02

Practical 2: Normal data

VIBASS

Rendered fromp2normal.Rmdusingknitr::rmarkdownon Feb 10 2025.

Last update: 2024-07-08
Started: 2023-07-02

Practical 3: Bayesian polynomial regression

VIBASS

Rendered fromp3.Rmdusingknitr::rmarkdownon Feb 10 2025.

Last update: 2024-07-08
Started: 2021-06-25

Practical 4: Simulation-based Bayesian inference

VIBASS

Rendered fromp4.Rmdusingknitr::rmarkdownon Feb 10 2025.

Last update: 2024-07-07
Started: 2021-07-01

Practical 5: Numerical approaches

VIBASS

Rendered fromp5.Rmdusingknitr::rmarkdownon Feb 10 2025.

Last update: 2024-07-08
Started: 2021-07-08

Practical 6: Software and GLMs

VIBASS

Rendered fromp6.Rmdusingknitr::rmarkdownon Feb 10 2025.

Last update: 2024-07-09
Started: 2021-07-08

Practical 7: Bayesian Hierarchical Modelling

VIBASS

Rendered fromp7.Rmdusingknitr::rmarkdownon Feb 10 2025.

Last update: 2024-07-08
Started: 2021-07-08

Practical 8: Optional Extra and Advanced Material

VIBASS

Rendered fromp8.Rmdusingknitr::rmarkdownon Feb 10 2025.

Last update: 2024-07-03
Started: 2021-07-08