cmahalanobis (version 0.5.0)

pvaluescjacc: Calculate the p_values matrix for each species, using Jaccard 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 Jaccard distance for the distances calculation.

Usage

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

Value

A list containing a matrix of p_values and, optionally, the plot.

Arguments

dataset

A dataframe.

formula

A factor which you want to calculate Jaccard distance.

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.

Examples

# Calculate p_values of "Species" variable in iris dataset
pvaluescjacc(iris,~Species, pvalue.method = "chisq", num.permutations = 100, num.bootstraps = 10)
# Calculate p_values of "am" variable in mtcars dataset
pvaluescjacc(mtcars,~am, pvalue.method = "chisq", num.permutations = 100, num.bootstraps = 10)