encodedata {NeuralEstimators} | R Documentation |
for data Z
with missing (NA
) entries, returns an augmented data set (U, W) where W encodes the missingness pattern as an indicator vector and U is the original data Z with missing entries replaced by a fixed constant c
.
The indicator vector W is stored in the second-to-last dimension of Z
, which should be singleton. If the second-to-last dimension is not singleton, then two singleton dimensions will be added to the array, and W will be stored in the new second-to-last dimension.
encodedata(Z, c = 0)
Z |
data containing |
c |
fixed constant with which to replace |
Augmented data set (U, W). If Z
is provided as a list, the return type will be a JuliaProxy
object; these objects can be indexed in the usual manner (e.g., using [[
), or converted to an R object using juliaGet()
(note however that juliaGet()
can be slow for large data sets).
## Not run:
library("NeuralEstimators")
Z <- matrix(c(1, 2, NA, NA, 5, 6, 7, NA, 9), nrow = 3)
encodedata(Z)
encodedata(list(Z, Z))
## End(Not run)