calculateDiscreteContinuousMI_Entropy: calculate mutual information between a discrete value (X) and...

In terminological/tidy-info-stats: Functions for manipulating information statistics

calculate mutual information between a discrete value (X) and a continuous value (Y) using estimates of differential entropy

Description

calculate mutual information between a discrete value (X) and a continuous value (Y) using estimates of differential entropy

Usage

calculateDiscreteContinuousMI_Entropy(
  df,
  discreteVars,
  continuousVar,
  entropyMethod = "Quantile",
  ...
)

Arguments

df	- may be grouped, in which case the grouping is interpreted as different types of discrete variable
discreteVars	- the column(s) of the categorical value (X) quoted by vars(...)
continuousVar	- the column of the continuous value (Y)
entropyMethod	- the method used to calculate the entropy (see ?tidyinfostats::calculateDiscreteEntropy) - defaults to "Grassberger"
collect	- unless TRUE this function will fail on dbplyr tables as there is no SQL implementation

Value

a dataframe containing the disctinct values of the groups of df, and for each group a mutual information column (I). If df was not grouped this will be a single entry

terminological/tidy-info-stats documentation built on Nov. 19, 2022, 11:23 p.m.