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To cite stagedtrees in publications use:
Carli F, Leonelli M, Riccomagno E, Varando G (2022). “The R Package stagedtrees for Structural Learning of Stratified Staged Trees.” Journal of Statistical Software, 102(6), 1-30. doi: 10.18637/jss.v102.i06 (URL: https://doi.org/10.18637/jss.v102.i06).
@Article{,
title = {The {R} Package {stagedtrees} for Structural Learning of Stratified Staged Trees},
author = {Federico Carli and Manuele Leonelli and Eva Riccomagno and Gherardo Varando},
journal = {Journal of Statistical Software},
year = {2022},
volume = {102},
number = {6},
pages = {1--30},
doi = {10.18637/jss.v102.i06},
}stagedtrees is a package that implements staged event trees, a class of probability models for categorical random variables.
# Install stable version from CRAN:
install.packages("stagedtrees")
# Or the development version from GitHub:
remotes::install_github("stagedtrees/stagedtrees")With the stagedtrees package it is possible to estimate (stratified) staged event trees from data, use them to compute probabilities, make predictions, visualize and compare different models.
library("stagedtrees")
tree <- Titanic |> full() |> stages_bhc() |> stndnaming(uniq = TRUE)
prob(tree, c(Survived="Yes"), conditional_on = c(Age="Adult"))
#> [1] 0.3107124
palette("Okabe-Ito")
par(mfrow = c(1,2))
plot(tree, col = "stages")
barplot(tree, var = "Survived", main = "P(Survived|-)", col = "stages")
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.