fit_ridge: Ridge regression estimator
In gapclosing: Estimate Gaps Under an Intervention
Description
Usage
Arguments
Value
References
Description
Not typically called by the user directly; called indirectly via other functions. Uses glmnet to fit a ridge regression with penalty chosen by cross-validation. Returns fitted values for the data in to_predict.
Usage
1
Arguments
data
Data frame containing the observed data
model_formula
A model formula object for the ridge regression to be fitted
to_predict
Data frame containing observations for which predictions are to be made. If NULL, defaults to the same as data.
Value
A list containing a glmnet model object fit and a vector fitted of fitted values for observations in to_predict.
References
Lundberg I (2021). "The gap-closing estimand: A causal approach to study interventions that close disparities across social categories." Sociological Methods and Research. Available at https://osf.io/gx4y3/.
Friedman J, Hastie T, Tibshirani R (2010). "Regularization Paths for Generalized Linear Models via Coordinate Descent." Journal of Statistical Software, 33(1), 1–22. https://www.jstatsoft.org/htaccess.php?volume=33&type=i&issue=01.
gapclosing documentation built on Oct. 11, 2021, 9:07 a.m.
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.
Description Usage Arguments Value References
Description
Not typically called by the user directly; called indirectly via other functions. Uses glmnet to fit a ridge regression with penalty chosen by cross-validation. Returns fitted values for the data in to_predict.
Usage
1 |
Arguments
data |
Data frame containing the observed data |
model_formula |
A model formula object for the ridge regression to be fitted |
to_predict |
Data frame containing observations for which predictions are to be made. If NULL, defaults to the same as |
Value
A list containing a glmnet model object fit and a vector fitted of fitted values for observations in to_predict.
References
Lundberg I (2021). "The gap-closing estimand: A causal approach to study interventions that close disparities across social categories." Sociological Methods and Research. Available at https://osf.io/gx4y3/.
Friedman J, Hastie T, Tibshirani R (2010). "Regularization Paths for Generalized Linear Models via Coordinate Descent." Journal of Statistical Software, 33(1), 1–22. https://www.jstatsoft.org/htaccess.php?volume=33&type=i&issue=01.
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.