predict.grpsurvOverlap: Model predictions based on a fitted 'grpsurvOverlap' object.
In grpregOverlap: Penalized Regression Models with Overlapping Grouped Covariates

Description Usage Arguments Details Author(s)

Similar to other predict methods, this function returns predictions from a fitted "grpsurvOverlap" object.

## S3 method for class 'grpsurvOverlap'
predict(object, X, type=c("link", "response", "survival",
        "median", "norm", "coefficients", "vars", "nvars", "groups", "ngroups"),
        latent = FALSE, lambda, which=1:length(object$lambda), ...)

Adoptted from predict.grpsurv:

`object`	Fitted `"grpsurvOverlap"` model object.
`X`	Matrix of values at which predictions are to be made. Not used for `type="coefficients"` or for some of the `type` settings in `predict`.
`latent`	Should plot the paths of latent coefficients? Default is TRUE. Note \hat{γ} is used as the label of y axis to represent latent coefficient vector.
`lambda`	Values of the regularization parameter `lambda` at which predictions are requested. For values of `lambda` not in the sequence of fitted models, linear interpolation is used.
`which`	Indices of the penalty parameter `lambda` at which predictions are required. By default, all indices are returned. If `lambda` is specified, this will override `which`.
`type`	Type of prediction: `"link"` returns the linear predictors; `"response"` gives the risk (i.e., exp(link)); `"survival"` returns the estimated survival function; `"median"` estimates median survival times. The other options are all identical to their `grpreg` counterparts: `"coefficients"` returns the coefficients; `"vars"` returns the indices for the nonzero coefficients; `"groups"` returns the indices for the groups with at least one nonzero coefficient; `"nvars"` returns the number of nonzero coefficients; `"ngroups"` returns the number of groups with at least one nonzero coefficient; `"norm"` returns the L2 norm of the coefficients in each group.
`...`	Not used.