predict_donor {imputeGeneric} | R Documentation |
Prediction for donor-based imputation
Description
This function is intended to be used inside of impute_unsupervised()
as
predict_fun
.
Usage
predict_donor(
ds_donors,
ds,
M = is.na(ds),
i,
donor_aggregation = "choose_random"
)
Arguments
ds_donors |
Data set with donors, normally generated by |
ds |
The data set to be imputed. Must be a data frame with column names. |
M |
Missing data indicator matrix |
i |
Index of row of |
donor_aggregation |
Type of donor aggregation. Can be one of 'choose_random' and 'average'. |
Value
The imputation values for row i
.
See Also
Examples
set.seed(123)
ds_mis <- data.frame(X = rnorm(10), Y = rnorm(10))
ds_mis[2:4, 1] <- NA
ds_mis[4:6, 2] <- NA
# default for ds_donors and predict_donors
ds_donors <- model_donor(ds_mis)
predict_donor(ds_donors, ds_mis, i = 2)
predict_donor(ds_donors, ds_mis, i = 4)
# with partly_complete, knn and average of neighbors
ds_donors <- model_donor(
ds_mis,
i = 5, model_arg = list(selection = "knn_partly_complete_rows", k = 2)
)
ds_donors
predict_donor(ds_donors, ds_mis, i = 5, donor_aggregation = "average")
[Package imputeGeneric version 0.1.0 Index]