bonferroni {ineqJD}

Point and synthetic Bonferroni indexes

Description

Computes the decomposition of the Bonferroni point inequality indexes of a statistical variable Y described in the object x.

Usage

bonferroni(x)

Arguments

x

An object of class "dataProcessed". x is usually the result of dataProcessing function. More details are given in the "Details" section and dataProcessing help page.

Details

bonferroni computes the decomposition of the Bonferroni point inequality indexes from the object x of class "dataProcessed". x is usually the result of dataProcessing function.

Value

index

String denoting computed index.

decomposition

Array containing the decompositions. The dimensions of decomposition are c(g, g, r, s) where g is the number of groups, r the number of different values of Y and s the number of sources.

x

Object of class dataProcessed passed as input.

Author(s)

Alberto Arcagni, Igor Valli.

References

Zenga M., Valli I. (2017). Joint decomposition by Subpopulations and Sources of the Point and Synthetic Bonferroni Inequality Measures. Statistics and Applications, XV (2), pp. 83-120.

See Also

gini and zenga for other inequality indexes and dataProcessing for the class "dataProcessed".

Examples

G <- c(1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 3, 3) # vector denoting group membership
X1 <- c(0, 0, 0, 500, 700, 300, 750, 1000, 500, 500, 500, 1000) # vector of the first source
X2 <- c(0, 0, 0, 500, 300, 700, 750, 500, 700, 700, 1000,600) # vector of the second source
data <- data.frame(G, X1, X2) # no sample weights are considered
x <- dataProcessing( # data preparation
  units = data[, c('X1', 'X2')],
  groups = data[, 'G'],
)
  
decomposition <- bonferroni(x)
decomposition