pvaluesceucl: Calculate the p_values matrix for each species, using the Euclidean distance as a base.

Description

This function takes a dataset, a factor, a p_value method, number of bootstraps and permutation when necessary, and returns a p_values matrix between each pair of species and a plot if the user select TRUE using Euclidean distance for the distances calculation.

Usage

pvaluesceucl(
  dataset,
  formula,
  pvalue.method = "chisq",
  num.permutations = 100,
  num.bootstraps = 10,
  plot = TRUE
)

Value

A list containing the p_values matrix and, optionally, the plot. #' @examples # Calculate p_values of "Species" variable in iris dataset pvaluesceucl(iris,~Species, pvalue.method = "chisq", num.permutations = 100, num.bootstraps = 10) # Calculate p_values of "am" variable in mtcars dataset pvaluesceucl(mtcars,~am, pvalue.method = "chisq", num.permutations = 100, num.bootstraps = 10)

Arguments

dataset: A dataframe.
formula: A factor which you want to calculate the Euclidean distances.
pvalue.method: A p_value method used to calculate the matrix, the default value is "chisq". Other methods are "permutation" and "bootstrap".
num.permutations: Number of permutation to specify if you select "permutation" in "pvalue.method". The default value is 100.
num.bootstraps: Number of bootstrap to specify if you select "bootstrap" in "p_value method". The default value is 10.
plot: if TRUE, plot the p_values heatmap. The default value is TRUE.