regress.func: Quadratic Programming Algorithm
In joeornstein/SRP: Stacked Regression and Poststratification
Description
Usage
Arguments
Value
View source: R/stackingFunctions.R
Description
Quadratic programming solution to stacking problem from Grimmer, Messing & Westwood (2017)
Usage
1
regress.func(Y, preds.var)
Arguments
Y
The outcome variable
preds.var
An n x k matrix of out-of-fold predictions of Y, where n is the length of Y, and k is th number of models
Value
The optimal stacking weights
joeornstein/SRP documentation built on Oct. 15, 2020, 8:30 p.m.
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Description Usage Arguments Value
View source: R/stackingFunctions.R
Description
Quadratic programming solution to stacking problem from Grimmer, Messing & Westwood (2017)
Usage
1 | regress.func(Y, preds.var)
|
Arguments
Y |
The outcome variable |
preds.var |
An n x k matrix of out-of-fold predictions of Y, where n is the length of Y, and k is th number of models |
Value
The optimal stacking weights
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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