R: Penalized regression object

penfit object {penalized} | R Documentation

## Penalized regression object

### Description

Stores the result of a call to `penalized`.

### Slots

`penalized`:

  Object of class "vector". Regression coefficients for the penalized covariates.

`unpenalized`:

  Object of class "vector". Regression coefficients for the unpenalized covariates.

`residuals`:

  Object of class "vector". Unstandardized residuals for each subject in the fitted model. Martingale residuals are given for the cox model.

`fitted`:

  Object of class "vector". Fitted values (means) for each subject in the fitted model. In the cox model, this slot holds the relative risks.

`lin.pred`:

  Object of class "vector". Linear predictors for each subject in the fitted model.

`loglik`:

  Object of class "numeric". Log likelihood of the fitted model. For the Cox model, reports the full likelihood rather than the partial likelihood.

`penalty`:

  Object of class "vector". L1 and L2 penalties of the fitted model.

`iterations`:

  Object of class "numeric". Number of iterations used in the fitting process.

`converged`:

  Object of class "logical". Whether the fitting process was judged to be converged.

`model`:

  Object of class "character". The name of the generalized linear model used.

`lambda1`:

  Object of class "vector". The lambda1 parameter(s) used.

`lambda2`:

  Object of class "vector". The lambda2 parameter(s) used.

`nuisance`:

  Object of class "list". The maximum likelihood estimates of any nuisance parameters in the model.

`weights`:

  Object of class "vector". The weights of the covariates used for standardization.

`formula`:

  Object of class "list". A named list containing the unpenalized and penalized formula objects, if present.

### Methods

basehaz

  (penfit): Returns the baseline hazard (a `data.frame`) if a cox model was fitted, `NULL` otherwise. An additional argument `center` (default (`TRUE`) can be used to give the survival curve at the covariate mean (`center = TRUE`) rather than at zero.

basesurv

  (penfit): Returns the baseline survival curve (a `breslow` object) if a cox model was fitted, `NULL` otherwise. An additional argument `center` (default (`TRUE`) can be used to give the survival curve at the covariate mean (`center = TRUE`) rather than at zero.

coef

  (penfit): Returns the regression coefficients. Accepts a second argument "which", that takes values "nonzero" (the default), "all", "penalized" or "unpenalized" for extracting only the non-zero, the penalized or the unpenalized regression coefficients. A third argument "standardize" (default FALSE) can be used to let the method return the regression coefficients for the standardized covariates.

coefficients

  (penfit): synonym for `coef` above.

fitted

  (penfit): Returns the fitted values for each subject (i.e. the predicted means). In the Cox model, this method returns the relative risks for each individual.

fitted.values

  (penfit): synonym for `fitted` above.

linear.predictors

  (penfit): Returns the linear predictors for each subject.

loglik

  (penfit): Returns the log likelihood of the fitted model.

penalty

  (penfit): Returns the L1 and L2 penalties of the fitted model.

residuals

  (penfit): Returns the residuals.

show

  (penfit): Summarizes the fitted model.

weights

  (penfit): Returns the weights used for standardization.

predict

  (penfit): Calculates predictions for new subjects. See `predict`.

### Author(s)

Jelle Goeman: j.j.goeman@lumc.nl

### See Also

`penalized`.

[Package penalized version 0.9-50 Index]