coef.xrnet: Get coefficient estimates from "xrnet" model object.

In USCbiostats/hierr: Hierarchical Regularized Regression

Get coefficient estimates from "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 'xrnet'
coef(object, p = NULL, pext = NULL, ...)

Arguments

object	A xrnet object.
p	vector of penalty values to apply to predictor variables.
pext	vector of penalty values to apply to external data variables.
...	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

data(GaussianExample)

fit_xrnet <- xrnet(
  x = x_linear,
  y = y_linear,
  external = ext_linear,
  family = "gaussian"
)

lambda1 <- fit_xrnet$penalty[10]
lambda2 <- fit_xrnet$penalty_ext[10]

coef_xrnet <- coef(
  fit_xrnet,
  p = lambda1,
  pext = lambda2,
)

USCbiostats/hierr documentation built on Dec. 12, 2023, 12:55 p.m.