pvaluescmanh: Calculate the p_values matrix or matrices (two or more) for...

In cmahalanobis: Calculate Distance Measures for DataFrames

Calculate the p_values matrix or matrices (two or more) for each factor inside variable or variables (two or more), using Manhattan distance as a base.

Description

Using the Manhattan distance for the distances calculation, this function takes a dataframe, a variable or variables (two or more), a p_value method such as "bootstrap" and "permutation" and returns the p_values matrix or matrices (two or more) between each pair of factors and a plot or plots (two or more) if the user select TRUE or leaves the parameter without argument.

Usage

pvaluescmanh(
  dataset,
  formula,
  pvalue.method = "permutation",
  plot = TRUE,
  seed = NULL,
  min_group_size = 3
)

Arguments

dataset	A dataframe.
formula	A variable or variables (two or more) with factors which you want to calculate the Manhattan distances matrix or matrices (two or more).
pvalue.method	A p_value method used to calculate the matrix or matrices (two or more), the default value is "permutation". Another method is "bootstrap".
plot	if TRUE, plot the p_values heatmap or heatmaps (two or more). The default value is TRUE.
seed	Optionally, set a seed for "bootstrap" and "permutation".
min_group_size	Minimum group size to maintain. The default value is 3, therefore groups, inside variables, with less than 3 observations will be discarded.

Value

A list containing a matrix or matrices (two or more) of p_values and, optionally, the plot.

Examples

# Example with iris dataset
data(iris)

# Calculate p_values of "Species" variable in iris dataset
pvaluescmanh(iris,~Species, pvalue.method = "bootstrap")

# Example with mtcars dataset
data(mtcars)

# Calculate p_values of "am" variable in mtcars dataset
pvaluescmanh(mtcars,~am, 
pvalue.method = "permutation", seed = 123)

cmahalanobis documentation built on Sept. 14, 2025, 5:09 p.m.