get_importance: Collect Variable Importance Metrics for Covariates Used in...
In milesdwilliams15/RFA: Estimate Average Treatment Effect via Random Forest Residualization
View source: R/get_importance.R
get_importance R Documentation
Collect Variable Importance Metrics for Covariates Used in Random Forest Adjustment
Description
This function returns variable importance metrics (either "impurity" or "permutation") for each of the covariates
included in random forest adjustment estimation with respect to the response
variable and the explanatory variable of interest.
Usage
get_importance(rfa)
Arguments
rfa
an 'rfa()' fitted object
Details
To return importance metrics, in 'rfa()' the argument 'importance' must be set to either "impurity" or "permutation" (quoted).
milesdwilliams15/RFA documentation built on Sept. 26, 2023, 4:31 a.m.
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View source: R/get_importance.R
| get_importance | R Documentation |
Collect Variable Importance Metrics for Covariates Used in Random Forest Adjustment
Description
This function returns variable importance metrics (either "impurity" or "permutation") for each of the covariates included in random forest adjustment estimation with respect to the response variable and the explanatory variable of interest.
Usage
get_importance(rfa)
Arguments
rfa |
an 'rfa()' fitted object |
Details
To return importance metrics, in 'rfa()' the argument 'importance' must be set to either "impurity" or "permutation" (quoted).
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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