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]

vibass_0.0.55.tar.gz
vibass_0.0.55.zip(r-4.5)vibass_0.0.55.zip(r-4.4)vibass_0.0.55.zip(r-4.3)
vibass_0.0.55.tgz(r-4.4-any)vibass_0.0.55.tgz(r-4.3-any)
vibass_0.0.55.tar.gz(r-4.5-noble)vibass_0.0.55.tar.gz(r-4.4-noble)
vibass_0.0.55.tgz(r-4.4-emscripten)vibass_0.0.55.tgz(r-4.3-emscripten)
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'))

Peer review:

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

Datasets:

On CRAN:

bayesian-inferenceteaching

3 exports 6 stars 1.24 score 78 dependencies 2 scripts

Last updated 2 months agofrom:28af94ba1f. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 13 2024
R-4.5-winNOTESep 13 2024
R-4.5-linuxNOTESep 13 2024
R-4.4-winNOTESep 13 2024
R-4.4-macNOTESep 13 2024
R-4.3-winNOTESep 13 2024
R-4.3-macNOTESep 13 2024

Exports:available_appssummary_tablevibass_app

Dependencies:attemptbase64encBayesXsrcbootbslibcachemclicolorspacecommonmarkconfigcpp11crayondigestdplyrevaluateextraDistrfansifarverfastmapfontawesomefsgenericsggplot2gluegolemgtableherehighrhtmltoolshttpuvisobandjquerylibjsonliteknitrlabelinglaterlatticelifecyclelme4magrittrMASSMatrixmemoisemgcvmimeminqamunsellnlmenloptrpillarpkgconfigpromisespurrrR2BayesXR6rappdirsRColorBrewerRcppRcppEigenrlangrprojrootrstudioapisassscalesshinysourcetoolsstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrxfunxtableyaml

Practical 1: Binary data

Rendered fromp1.Rmdusingknitr::rmarkdownon Sep 13 2024.

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

Practical 2: Count data

Rendered fromp2count.Rmdusingknitr::rmarkdownon Sep 13 2024.

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

Practical 2: Normal data

Rendered fromp2normal.Rmdusingknitr::rmarkdownon Sep 13 2024.

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

Practical 3: Bayesian polynomial regression

Rendered fromp3.Rmdusingknitr::rmarkdownon Sep 13 2024.

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

Practical 4: Simulation-based Bayesian inference

Rendered fromp4.Rmdusingknitr::rmarkdownon Sep 13 2024.

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

Practical 5: Numerical approaches

Rendered fromp5.Rmdusingknitr::rmarkdownon Sep 13 2024.

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

Practical 6: Software and GLMs

Rendered fromp6.Rmdusingknitr::rmarkdownon Sep 13 2024.

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

Practical 7: Bayesian Hierarchical Modelling

Rendered fromp7.Rmdusingknitr::rmarkdownon Sep 13 2024.

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

Practical 8: Optional Extra and Advanced Material

Rendered fromp8.Rmdusingknitr::rmarkdownon Sep 13 2024.

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