largestRemainders: Largest Remainders Methods of Allocating Seats Proportionally

In danielmarcelino/SciencesPo: A Tool Set for Analyzing Political Behavior Data

Description

Computes the largest remainders method for a variety of formulas of allocating seats proportionally.

Usage

largestRemainders(parties = NULL, votes = NULL, seats = NULL,
  method = c("hare", "droop", "hagb", "imperiali", "imperiali.adj"),
  threshold = 0, ...)

## Default S3 method:
largestRemainders(parties = NULL, votes = NULL,
  seats = NULL, method = c("hare", "droop", "hagb", "imperiali",
  "imperiali.adj"), threshold = 0, ...)

Arguments

parties	A character vector for parties labels or candidates in the order as votes. If NULL, a random combination of letters will be assigned.
votes	A numeric vector for the number of formal votes received by each party or candidate.
seats	The number of seats to be filled (scalar or vector).
method	A character name for the method to be used. See details.
threshold	A numeric value between (0~1). Default is set to 0.
...	Additional arguements (currently ignored)

Details

The following methods are available:

• "droop"Droop quota method

• "hare"Hare method

• "hagb"Hagenbach-Bischoff

• "imperiali"Imperiali quota (do not confuse with the Italian Imperiali, which is a highest averages method)

• "imperiali.adj"Reinforced or adjusted Imperiali quota

Value

A data.frame of length parties containing apportioned integers (seats) summing to seats.

Author(s)

Daniel Marcelino, [e-mail].

References

Gallagher, Michael (1992). "Comparing Proportional Representation Electoral Systems: Quotas, Thresholds, Paradoxes and Majorities". British Journal of Political Science, 22, 4, 469-496.

Lijphart, Arend (1994). Electoral Systems and Party Systems: A Study of Twenty-Seven Democracies, 1945-1990. Oxford University Press.

See Also

highestAverages, proportionality, PoliticalDiversity. For more details see the Indices vignette: vignette('Indices', package = 'SciencesPo').

Examples

# Let's create a data.frame with typical election results
# with the following parties and votes to return 10 seats:

my_election_data <- data.frame(
party=c("Yellow", "White", "Red", "Green", "Blue", "Pink"),
votes=c(47000, 16000,	15900,	12000,	6000,	3100))

largestRemainders(my_election_data$party,
my_election_data$votes, seats = 10,  method="droop")

with(my_election_data, largestRemainders(party,
votes, seats = 10,  method="hare"))

danielmarcelino/SciencesPo documentation built on Oct. 20, 2019, 1:15 a.m.