summary.causalWeights {causalOT} | R Documentation |
Summary diagnostics for causalWeights
Description
Summary diagnostics for causalWeights
print.summary_causalWeights
plot.summary_causalWeights
Usage
## S3 method for class 'causalWeights'
summary(
object,
r_eff = NULL,
penalty,
p = 2,
cost = NULL,
debias = TRUE,
online.cost = "auto",
diameter = NULL,
niter = 1000,
tol = 1e-07,
...
)
## S3 method for class 'summary_causalWeights'
print(x, ...)
## S3 method for class 'summary_causalWeights'
plot(x, ...)
Arguments
object |
an object of class causalWeights |
r_eff |
The r_eff used in the PSIS calculation. See |
penalty |
The penalty parameter to use |
p |
The power of the Lp distance to use. Overridden by argument |
cost |
A user supplied cost function. Should take arguments |
debias |
Should debiased optimal transport distances be used. TRUE or FALSE |
online.cost |
Should the cost be calculated online? One of "auto","tensorized", or "online". |
diameter |
the diameter of the covariate space. Default is NULL. |
niter |
the number of iterations to run the optimal transport distances |
tol |
the tolerance for convergence for the optimal transport distances |
... |
Not used |
x |
an object of class "summary_causalWeights" |
Value
The summary method returns an object of class "summary_causalWeights".
Functions
-
print(summary_causalWeights)
: print method -
plot(summary_causalWeights)
: plot method
Examples
if(torch::torch_is_installed()) {
n <- 2^6
p <- 6
overlap <- "high"
design <- "A"
estimand <- "ATE"
#### get simulation functions ####
original <- Hainmueller$new(n = n, p = p,
design = design, overlap = overlap)
original$gen_data()
weights <- calc_weight(x = original, estimand = estimand, method = "Logistic")
s <- summary(weights)
plot(s)
}