penfit: Penalized regression object

In penalized: L1 (Lasso and Fused Lasso) and L2 (Ridge) Penalized Estimation in GLMs and in the Cox Model

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: [e-mail]

See Also

penalized.

penalized documentation built on April 23, 2022, 5:05 p.m.