nslphom_dual | R Documentation |
Estimates RxC vote transfer matrices (ecological contingency tables) with nslphom_dual
nslphom_dual( votes_election1, votes_election2, iter.max = 10, min.first = FALSE, integers = FALSE, solver = "lp_solve", integers.solver = "symphony", tol = 10^-5, ... )
votes_election1 |
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_election2 |
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. In general, The sum by rows of |
iter.max |
Maximum number of iterations to be performed in each dual linear program.
The process ends independently in each system when either the number of iterations reaches
iter.max or when the maximum variation between two consecutive estimates of the
probability transfer matrix is less than |
min.first |
A TRUE/FALSE value. If FALSE, the matrix associated with the minimum |
integers |
A TRUE/FALSE value that indicates whether the problem is solved in integer values in each iteration: zero (lphom) and intermediate and final (including unit) solutions. If TRUE, the initial LP matrices are approximated in each iteration to the closest integer solution solving the corresponding Integer Linear Program. Default, FALSE. |
solver |
A character string indicating the linear programming solver to be used, only
|
integers.solver |
A character string indicating the linear programming solver to be used to approximate
to the closest integer solution, only |
tol |
Maximum deviation allowed between two consecutive iterations. The process ends when the maximum
variation between two proportions for the estimation of the transfer matrix between two consecutive
iterations is less than |
... |
Other arguments to be passed to the function. Not currently used. |
A list with the following components
VTM.votes.w |
The matrix of order JxK with the estimated cross-distribution of votes of elections 1 and 2, attained weighting the two dual solutions using as weights the corresponding HTEe estimates. |
VTM.votes.units.w |
The array of order JxKxI with the local estimated cross-distributions of votes of elections 1 and 2 by unit, attained weighting the two dual solutions using as weights the corresponding HTEe estimates. |
VTM.votes.a |
The matrix of order JxK with the estimated cross-distribution of votes of elections 1 and 2, attained simple averaging the two dual solutions. |
VTM.votes.units.a |
The matrix of order JxKxI with the estimated cross-distributions of votes of elections 1 and 2 by unit, attained weighting the two dual solutions using as weights the corresponding HTEe estimates. |
HETe.w |
Estimated heterogeneity index associated to the |
HETe.a |
Estimated heterogeneity index associated to the |
VTM12.w |
The matrix of order JxK with the estimated row-standardized proportions of vote transitions from election 1
to election 2 associated to the |
VTM21.w |
The matrix of order KxJ with the estimated row-standardized proportions of vote transitions from election 2
to election 1 associated to the |
VTM12.a |
The matrix of order JxK with the estimated row-standardized proportions of vote transitions from election 1
to election 2 associated to the |
VTM21.a |
The matrix of order KxJ with the estimated row-standardized proportions of vote transitions from election 2
to election 1 associated to the |
nslphom.object.12 |
The output of the |
nslphom.object.21 |
The output of the |
inputs |
A list containing all the objects with the values used as arguments by the function. |
Jose M. Pavia, pavia@uv.es
Rafael Romero rromero@eio.upv.es
Pavia, JM and Romero, R (2021). Symmetry estimating R×C vote transfer matrices from aggregate data, mimeo.
nslphom
lphom_dual
tslphom_dual
lphom_joint
tslphom_joint
nslphom_joint
Other linear programing ecological inference functions:
lclphom()
,
lp_apriori()
,
lphom_dual()
,
lphom_joint()
,
lphom()
,
nslphom_joint()
,
nslphom()
,
tslphom_dual()
,
tslphom_joint()
,
tslphom()
x <- France2017P[, 1:8] y <- France2017P[, 9:12] y[,1] <- y[,1] - (rowSums(y) - rowSums(x)) mt <- nslphom_dual(x, y) mt$VTM.votes.w mt$HETe.w
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