Impute_missing_covs_rf: Impute missing covariate values.
In qureshlatif/QSLpersonal: Quresh's Personal Package
View source: R/Impute_missing_covs_rf.R
Impute_missing_covs_rf R Documentation
Impute missing covariate values.
Description
Imputes missing covariate values using a Random Forest model informed with specified covariates.
Usage
Impute_missing_covs_rf(dat, v.fill, v.inform)
Arguments
dat
Data frame or matrix containing covariate values.
v.fill
String naming the variable in 'dat' with missing values to be imputed.
v.inform
String vector naming the covariates in 'dat' to be used for informing a random forest model to impute missing values.
Value
Data frame or matrix of same dimensions as 'dat' but with missing values imputed.
Note
R packages required: randomForest, dplyr, stringr
Author(s)
Quresh S. Latif
qureshlatif/QSLpersonal documentation built on Sept. 12, 2023, 6:24 p.m.
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View source: R/Impute_missing_covs_rf.R
| Impute_missing_covs_rf | R Documentation |
Impute missing covariate values.
Description
Imputes missing covariate values using a Random Forest model informed with specified covariates.
Usage
Impute_missing_covs_rf(dat, v.fill, v.inform)
Arguments
dat |
Data frame or matrix containing covariate values. |
v.fill |
String naming the variable in 'dat' with missing values to be imputed. |
v.inform |
String vector naming the covariates in 'dat' to be used for informing a random forest model to impute missing values. |
Value
Data frame or matrix of same dimensions as 'dat' but with missing values imputed.
Note
R packages required: randomForest, dplyr, stringr
Author(s)
Quresh S. Latif
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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