coef.tune_xrnet {xrnet} | R Documentation |
Get coefficient estimates from "tune_xrnet" model object.
Description
Returns coefficients from 'xrnet' model. Note that we currently only support returning coefficient estimates that are in the original path(s).
Usage
## S3 method for class 'tune_xrnet'
coef(object, p = "opt", pext = "opt", ...)
Arguments
object |
A |
p |
vector of penalty values to apply to predictor variables. Default is optimal value in tune_xrnet object. |
pext |
vector of penalty values to apply to external data variables. Default is optimal value in tune_xrnet object. |
... |
pass other arguments to xrnet function (if needed). |
Value
A list with coefficient estimates at each of the requested penalty combinations.
beta0 |
matrix of first-level intercepts indexed by penalty values, NULL if no first-level intercept in original model fit. |
betas |
3-dimensional array of first-level penalized coefficients indexed by penalty values. |
gammas |
3-dimensional array of first-level non-penalized coefficients indexed by penalty values, NULL if unpen NULL in original model fit. |
alpha0 |
matrix of second-level intercepts indexed by penalty values, NULL if no second-level intercept in original model fit. |
alphas |
3-dimensional array of second-level external data coefficients indexed by penalty values, NULL if external NULL in original model fit. |
Examples
## Cross validation of hierarchical linear regression model
data(GaussianExample)
## 5-fold cross validation
cv_xrnet <- tune_xrnet(
x = x_linear,
y = y_linear,
external = ext_linear,
family = "gaussian",
control = xrnet_control(tolerance = 1e-6)
)
## Get coefficient estimates at optimal penalty combination
coef_opt <- coef(cv_xrnet)