rsq.causalTree: Plots the Approximate R-Square for the Different Splits
In swager/causalForest: Causal Trees and Forests
Description
Usage
Arguments
Side Effects
Note
Examples
Description
Produces 2 plots. The first plots the r-square (apparent and
apparent - from cross-validation) versus the number of splits.
The second plots the Relative Error(cross-validation) +/- 1-SE from
cross-validation versus the number of splits.
Usage
1
Arguments
x
fitted model object of class "causalTree". This is assumed to be the result
of some function that produces an object with the same named
components as that returned by the causalTree function.
Side Effects
Two plots are produced.
Note
The labels are only appropriate for the "anova" method.
Examples
1
2
z.auto <- causalTree(Mileage ~ Weight, car.test.frame)
rsq.causalTree(z.auto)
swager/causalForest documentation built on May 30, 2019, 9:32 p.m.
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Description Usage Arguments Side Effects Note Examples
Description
Produces 2 plots. The first plots the r-square (apparent and apparent - from cross-validation) versus the number of splits. The second plots the Relative Error(cross-validation) +/- 1-SE from cross-validation versus the number of splits.
Usage
1 |
Arguments
x |
fitted model object of class |
Side Effects
Two plots are produced.
Note
The labels are only appropriate for the "anova" method.
Examples
1 2 | z.auto <- causalTree(Mileage ~ Weight, car.test.frame)
rsq.causalTree(z.auto)
|
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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