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Inequality and Diversity Measures

Source: R/inequ.R
concstats_inequ.Rd

A set of different inequality and diversity measures.

Usage

concstats_inequ(x, normalized = TRUE, type = c("entropy", "gini",
 "simpson", "palma", "grs", "all"), na.rm = TRUE, digits = NULL)

Arguments

x

A non-negative numeric vector.

normalized

Logical. Argument of the functions concstats_entropy, concstats_gini specifying whether or not a normalized value is required. Must be either TRUE or FALSE. The default is TRUE.

type

A character string of the measure to be calculated, defaults to concstats_entropy. Input is not case-sensitive.

na.rm

A logical vector that indicates whether NA values should be excluded or not. Must be either TRUE or FALSE. The default is TRUE. If set to FALSE the computation yields a message if the vector contains NA values. NAs will be removed for further computations.

digits

A non-null value for digits specifies the minimum number of significant digits to be printed in values. The default is NULL and will use base R print option. Significant digits defaults to 7. Values are restricted between 1 and default value.

Value

The calculated numeric measure or a data frame

Details

  • concstats_inequ is a wrapper for the proposed inequality measures. All measures can be accessed individually.

  • concstats_entropy() returns the Shannon entropy. concstats_entropy You can normalize the entropy measures by setting normalized = TRUE.

  • concstats_gini() calculates the gini coefficient. concstats_gini You can normalize the gini measures by setting normalized = TRUE.

  • concstats_simpson() calculates the gini-simpson index.

  • concstats_palma() calculates the palma ratio of inequality.

  • concstats_grs() calculates an alternative concentration measure.

  • concstats_all_inequ() returns all measures in a one step procedure. For more details or references please see the help page of the respective function.

See also

concstats_concstats(),concstats_mstruct(),concstats_comp()

Other Concentration and inequality measures: concstats_all_inequ(), concstats_entropy(), concstats_gini(), concstats_grs(), concstats_palma(), concstats_simpson()

Examples

# a vector of market shares
x <- c(0.4, 0.2, 0.25, 0.1, 0.05)

# Calculate the Palma ratio
concstats_inequ(x, type = "palma")
#> [1] 2.666667

# Calculate the entropy measure directly
concstats_inequ(x, normalized = TRUE, type = "entropy")
#> [1] 0.879203

# Calculate the group measures
concstats_inequ(x, type = "all", digits = 2)
#>         Measure Value
#> 1       Entropy  0.88
#> 2    Gini Index  0.43
#> 3 Simpson Index  0.72
#> 4   Palma Ratio  2.67
#> 5           GRS  0.40