R/iris2-data.R

In divoRce: Diagnosing Separation Phenomena in Categorical Response Models

#' Adapted Iris Dataset
#'
#' This dataset is an adaptation of the famous Iris dataset. The original dataset contains measurements 
#' of iris flowers from three different species. In this adaptation, the dataset has been modified to 
#' create an ordinal response variable based on petal length, categorizing it into three groups: Low, 
#' Medium, and High, so that it shows separation. The dataset consists of five predictor variables and one ordinal response variable.
#'
#' @format A data frame with 150 rows and 6 coumns/variables:
#' \describe{
#'   \item{y}{An ordered factor representing the petal length category:
#'     \itemize{
#'       \item Low: Petal length less than 2.5
#'       \item Medium: Petal length between 2.5 and 5.0
#'       \item High: Petal length greater than 5.0
#'     }}
#'   \item{Sepal.Length}{Numeric. The length of the sepal in centimeters.}
#'   \item{Sepal.Width}{Numeric. The width of the sepal in centimeters.}
#'   \item{Petal.Length}{Numeric. The length of the petal in centimeters.}
#'   \item{Petal.Width}{Numeric. The width of the petal in centimeters.}
#'   \item{Species}{Categorical. The species of Iris.}
#' }
#'
#' @source The original Iris dataset is available as data(iris) in R 
#' @examples
#' # View the structure of the dataset
#' str(iris2)
#' @name iris2
#' @docType data
#' @keywords datasets
#' @usage data(iris2)
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