get_probabilities {coalitions}R Documentation

Wrapper for calculation of coalition probabilities from survey

Description

Given a table with simulations in the rows and coalitions in the columns, this function returns the coalition probabilities for a specified coalition, by default excluding superior coalitions first

Usage

get_probabilities(
  x,
  coalitions = list(c("cdu"), c("cdu", "fdp"), c("cdu", "fdp", "greens"), c("spd"),
    c("spd", "left"), c("spd", "left", "greens")),
  nsim = 1e+05,
  distrib.fun = sls,
  seats_majority = 300L,
  seed = as.numeric(now()),
  correction = NULL
)

Arguments

x

A table containing one row per survey and survey information in long format in a separate column named survey.

coalitions

A list of coalitions for which coalition probabilities should be calculated. Each list entry must be a vector of party names. Those names need to correspond to the names in majority_df.

nsim

number of simulations

distrib.fun

Function to calculate seat distribution. Defaults to sls (Sainte-Lague/Schepers).

seats_majority

The number of seats needed to obtain majority.

seed

sets seed

correction

A positive number. If not NULL, each sample from the Dirichlet distribution will be additionally "corrected" by a random number from U(-1*correction, 1*correction). This can be used to introduce extra variation which might be useful due to rounding errors from reported survey results (or add an additional source of variation in general).

See Also

calculate_prob

Examples

library(coalitions)
library(dplyr)
# get the latest survey for a sample of German federal election polls
surveys <- get_latest(surveys_sample)
# calculate probabilities for two coalitions
probs <- get_probabilities(surveys,
                           coalitions = list(c("cdu", "fdp"),
                                             c("spd", "left", "greens")),
                           nsim = 100) # ensure fast runtime with only 100 simulations
probs %>% tidyr::unnest("probabilities")

[Package coalitions version 0.6.20 Index]