View source: R/mice.impute.rfpred.cate.R
mice.impute.rfpred.cate | R Documentation |
Please note that functions with names starting with "mice.impute" are exported to be visible for the mice sampler functions. Please do not call these functions directly unless you know exactly what you are doing.
For categorical variables only.
Part of project RfEmpImp
, the function mice.impute.rfpred.cate
is for categorical variables, performing imputation based on predicted
probabilities for the categories.
mice.impute.rfpred.cate( y, ry, x, wy = NULL, num.trees.cate = 10, use.pred.prob.cate = TRUE, forest.vote.cate = FALSE, pre.boot = TRUE, num.threads = NULL, ... )
y |
Vector to be imputed. |
ry |
Logical vector of length |
x |
Numeric design matrix with |
wy |
Logical vector of length |
num.trees.cate |
Number of trees to build for categorical variables,
default to |
use.pred.prob.cate |
Logical, |
forest.vote.cate |
Logical, |
pre.boot |
Perform bootstrap prior to imputation to get 'proper'
multiple imputation, i.e. accommodating sampling variation in estimating
population regression parameters (see Shah et al. 2014).
It should be noted that if |
num.threads |
Number of threads for parallel computing. The default is
|
... |
Other arguments to pass down. |
RfEmpImp
Imputation sampler for: categorical variables based on
predicted probabilities.
Vector with imputed data, same type as y
, and of length
sum(wy)
.
Shangzhi Hong
Hong, Shangzhi, et al. "Multiple imputation using chained random forests." Preprint, submitted April 30, 2020. https://arxiv.org/abs/2004.14823.
Shah, Anoop D., et al. "Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study." American journal of epidemiology 179.6 (2014): 764-774.
Malley, James D., et al. "Probability machines." Methods of information in medicine 51.01 (2012): 74-81.
# Prepare data mtcars.catmcar <- mtcars mtcars.catmcar[, c("gear", "carb")] <- gen.mcar(mtcars.catmcar[, c("gear", "carb")], warn.empty.row = FALSE) mtcars.catmcar <- conv.factor(mtcars.catmcar, c("gear", "carb")) # Perform imputation impObj <- mice(mtcars.catmcar, method = "rfpred.cate", m = 5, maxit = 5, maxcor = 1.0, eps = 0, remove.collinear = FALSE, remove.constant = FALSE, printFlag = FALSE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.