Estimates RxC vote transfer matrices (ecological contingency tables) with tslphom_joint
tslphom_joint(
votes_election1,
votes_election2,
integers = FALSE,
solver = "lp_solve",
integers.solver = "symphony",
...
)A list with the following components
A matrix of order JxK with the estimated cross-distribution of votes of elections 1 and 2.
The estimated heterogeneity index associated to the VTM.votes solution.
The matrix of order JxK with the estimated row-standardized proportions of vote transitions from election 1 to election 2 associated to the VTM.votes solution.
The matrix of order KxJ with the estimated row-standardized proportions of vote transitions from election 2 to election 1 associated to the VTM.votes solution.
An array of order JxKxI with the estimated matrix of cross-distributions of votes of elections 1 and 2 attained for each unit after congruently adjusting the lphom_joint() initial estimate.
A matrix of order IxK measuring in each unit a distance to the homogeneity hypothesis. That is, the differences under the homogeneity hypothesis between the actual recorded results and the expected results in each territorial unit for each option of election two. The matrix Eik.
A matrix of order IxJ measuring in each unit a distance to the homogeneity hypothesis. That is, the differences under the homogeneity hypothesis between the actual recorded results and the expected results in each territorial unit for each option of election one. The matrix Eij.
A list of two matrices of order JxK and two arrays of order JxKxI containing for each vote transition the lower and upper allowed proportions given the observed aggregates.
A list containing all the objects with the values used as arguments by the function.
A list with the main outputs produced by lphom_joint().
data.frame (or matrix) of order IxJ with the counts to be initially
mapped to rows. When estimating vote transfer matrices, the votes gained by
the J political options competing on election 1 (or origin) in the I
territorial units considered. The sum by rows of votes_election1 and
votes_election2 must coincide.
data.frame (or matrix) of order IxK with the counts to be initially mapped
to columns. When estimating vote transfer matrices, the votes gained by
the K political options competing on election 2 (or destination) in the I
territorial units considered. The sum by rows of votes_election1 and
votes_election2 must coincide.
A TRUE/FALSE value that indicates whether the problem is solved in integer values
in both iterations: zero (lphom) and final (including unit) solutions. If TRUE, the LP matrices
are approximated to the closest integer solution solving the corresponding Integer Linear Program.
Default, FALSE.
A character string indicating the linear programming solver to be used, only
lp_solve and symphony are allowed. By default, lp_solve. The package Rsymphony
needs to be installed for the option symphony to be used.
A character string indicating the linear programming solver to be used to approximate
to the closest integer solution, only symphony and lp_solve are allowed.
By default, symphony. The package Rsymphony needs to be installed for the option symphony
to be used. Only used when integers = TRUE.
Other arguments to be passed to the function. Not currently used.
Jose M. Pavia, pavia@uv.es
Rafael Romero rromero@eio.upv.es
Pavia, JM and Romero, R (2024). Symmetry estimating RxC vote transfer matrices from aggregate data. Journal of the Royal Statistical Society, Series A – Statistics in Society, 187(4), 919-943. tools:::Rd_expr_doi("10.1093/jrsssa/qnae013")
tslphom lphom_dual tslphom_dual nslphom_dual lphom_joint nslphom_joint
Other linear programing ecological inference functions:
lclphom(),
lp_apriori(),
lphom_dual(),
lphom_joint(),
lphom(),
nslphom_dual(),
nslphom_joint(),
nslphom(),
rslphom(),
tslphom_dual(),
tslphom()
x <- France2017P[, 1:8]
y <- France2017P[, 9:12]
y[,1] <- y[,1] - (rowSums(y) - rowSums(x))
mt <- tslphom_joint(x, y)
mt$VTM.votes
mt$HETe
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