Shiny module to build and analyse conditional inference trees

The module builds a conditional inference trees according to several parameter inputs. Then it plots the tree and computes performance measures, variable importance, checks the stability and return the code to reproduce the analyses.

ctreeUI(id)

ctreeServer(id, data, name)

Arguments

id

Module id. See shiny::callModule().

data

shiny::reactive() function returning a data.frame to use for the analyses.

name

shiny::reactive() function returning a character string representing data name.

References

Hothorn T, Hornik K, Van De Wiel MA, Zeileis A. "A lego system for conditional inference". The American Statistician. 60:257–263, 2006.

Hothorn T, Hornik K, Zeileis A. "Unbiased Recursive Partitioning: A Conditional Inference Framework". Journal of Computational and Graphical Statistics, 15(3):651-674, 2006.

Author

Nicolas Robette

See also

ictree

Examples

library(shiny)
library(moreparty)

data(titanic)

ui <- fluidPage(
  titlePanel("Conditional inference trees"),
  ctreeUI(id = "ctree_app")
)

server <- function(input, output, session) {
  rv <- reactiveValues(
    data = titanic,
    name = deparse(substitute(titanic))
  )
  ctreeServer(id = "ctree_app", reactive(rv$data), reactive(rv$name))
}

if (interactive())
  shinyApp(ui, server)