simula_BPF {eiCircles} | R Documentation |
Simulate RxC Tables from Overdispersed-Multinomial Models
Description
Generates at random a set of RxC tables with the joint distribution of voters in two elections according to the model proposed in Forcina et al. (2012), as extension of Brown and Payne (1986), under the assumption that local units are homogeneous (no covariates). Results in the first election may be provided by the user or generated at random according to the overdispersed multinomial model.
Usage
simula_BPF(
n.units,
TM,
prop1,
polling.sizes,
theta1 = 0.1,
theta2 = 0.1,
cs = 50,
noise = 0,
simplify = FALSE,
...
)
Arguments
n.units |
Either a positive integer number, |
TM |
A row-standardized RxC matrix with the underlying global transition probabilities of the simulated elections. If the matrix is not row-standardized, it is internally row-standardized by the function. |
prop1 |
A vector of length R with the initial assumed probabilities of voting (to be simulated) for each of the R competing options in the first election. If the provided vector is not a set of probabilities (i.e., a vector of positive numbers adding to 1), it is internally standardized by the function. |
polling.sizes |
Either a vector of two components with two positive integer
numbers indicating the minimum and maximum number of voters
for each unit or a vector of length |
theta1 |
A number between 0 and 1 used as the overdispersion parameter.
This parameter is employed by the underlying Dirichlet distribution,
in conjunction with |
theta2 |
Either a single number between 0 and 1 or a vector of length |
cs |
A positive number indicating the average number of cluster size. Default, |
noise |
Either a single number between 0 and 1 or a vector of length |
simplify |
A TRUE/FALSE argument indicating whether the simulated RxCxK array of counts by polling unit should be rearranged as a matrix of order Kx(RC). Default, FALSE. |
... |
Other arguments to be passed to the function. Not currently used. |
Value
A list with the following components
votes1 |
A matrix of order KxR with the results simulated in each polling unit for the first election. |
votes2 |
A matrix of order KxC with the results simulated in each polling unit for the second election.. |
TM.global |
A matrix of order RxC with the actual simulated global transfer matrix of counts. |
TM.units |
An array of order RxCxK with the simulated transfer matrices of votes by polling unit. If
|
inputs |
A list containing all the objects with the values used as arguments by the function. |
Author(s)
Antonio Forcina, forcinarosara@gmail.com
Jose M. Pavia, pavia@uv.es
References
Brown, P. and Payne, C. (1986). Aggregate data, ecological regression and voting transitions. Journal of the American Statistical Association, 81, 453–460. doi:10.1080/01621459.1986.10478290
Forcina, A., Gnaldi, M. and Bracalente, B. (2012). A revised Brown and Payne model of voting behaviour applied to the 2009 elections in Italy. Statistical Methods & Applications, 21, 109–119. doi:10.1007/s10260-011-0184-x
See Also
Other simulators for ecological inference overdispersed-multinomial models:
simula_BPF_with_deviations()
Examples
TMg <- matrix(c(0.6, 0.1, 0.3, 0.1, 0.7, 0.2, 0.1, 0.1, 0.8),
byrow = TRUE, nrow = 3)
example <- simula_BPF(n.units = 100, TM = TMg, prop1 = c(0.3, 0.3, 0.4),
polling.sizes = c(750, 850))