mat2targets | R Documentation |
In a data set with n
measurements of p
variables, intervened
variables can be specified in two ways:
with a logical
intervention matrix of dimension
n \times p
, where the entry [i, j]
indicates whether
variable j
has been intervened in measurement i
; or
with a list of (unique) intervention targets and a
p
-dimensional vector indicating the indices of the intervention
targets of the p
measurements.
The function mat2targets
converts the first representation to the
second one, the function targets2mat
does the reverse conversion. The
second representation can be used to create scoring objects (see
Score
) and to run causal inference methods based on
interventional data such as gies
or simy
.
mat2targets(A)
targets2mat(p, targets, target.index)
A |
Logical matrix with |
p |
Number of variables |
targets |
List of unique intervention targets |
target.index |
Vector of intervention target indices. The intervention
target of data point |
mat2targets
returns a list with two components:
targets |
A list of unique intervention targets. |
target.index |
A vector of intervention target indices. The intervention
target of data point |
Alain Hauser (alain.hauser@bfh.ch)
Score
, gies
, simy
## Specify interventions using a matrix
p <- 5
n <- 10
A <- matrix(FALSE, nrow = n, ncol = p)
for (i in 1:n) A[i, (i-1) %% p + 1] <- TRUE
## Generate list of intervention targets and corresponding indices
target.list <- mat2targets(A)
for (i in 1:length(target.list$target.index))
sprintf("Intervention target of %d-th data point: %d",
i, target.list$targets[[target.list$target.index[i]]])
## Convert back to matrix representation
all(A == targets2mat(p, target.list$targets, target.list$target.index))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.