shrink (version 1.2.3)

predict.shrink: Predict Method for Objects of Class shrink

Description

Obtains predictions from shrunken regression coefficients from an object of class shrink. This class of objects is returned by the shrink function. Objects of this class have methods for the functions coef, predict, print, summary, and vcov.

Usage

# S3 method for shrink
predict(
  object,
  newdata = NULL,
  type = c("link", "response", "lp", "risk", "expected", "terms"),
  shrinktype = NULL,
  terms = NULL,
  na.action = na.pass,
  collapse,
  safe = FALSE,
  ...
)

Value

A vector or matrix of predictions.

Arguments

object

an object of class shrink.

newdata

a data frame for which predictions are obtained, otherwise predictions are based on the data stored in object.

type

the type of prediction required.

shrinktype

the type of shrinkage requested, if the object was obtained with type = "all", either "parameterwise" or "global".

terms

with type = "terms" by default all terms are returned. A character vector specifies which terms are to be returned.

na.action

function determining what should be done with missing values in newdata. The default is to include all observations.

collapse

if family = coxph or Cox, an optional vector of subject identifiers. If specified, the output will contain one entry per subject rather than one entry per observation.

safe

option from predict.mfp.

...

additional arguments to be passed to methods.

See Also

shrink, coef.shrink, print.shrink, summary.shrink, vcov.shrink

Examples

data("GBSG")
library("mfp")

fit <- mfp(Surv(rfst, cens) ~ fp(age, df = 4, select = 0.05) +
           fp(prm, df = 4, select = 0.05), family = cox, data = GBSG)

dfbeta.global <- shrink(fit, type = "global",  method = "dfbeta")
dfbeta.pw     <- shrink(fit, type = "parameterwise", method = "dfbeta")
dfbeta.join   <- shrink(fit, type = "parameterwise", method = "dfbeta",
                        join=list(c("age.1", "age.2")))

age <- 30:80
newdat <- data.frame(age = age, prm = 0)
refdat <- data.frame(age = 50, prm = 0)

# unshrunken
plot(age, predict(fit, newdata = newdat, type = "lp") -
       predict(fit, newdata = refdat, type = "lp"), xlab = "Age",
     ylab = "Log hazard relative to 50 years", type = "l", lwd = 2)

# globally shrunken
lines(age, predict(dfbeta.global,newdata = newdat, type = "lp") -
        predict(dfbeta.global, newdata = refdat, type = "lp"), lty = 3, col = "red", lwd = 2)

# jointly shrunken
lines(age, predict(dfbeta.join, newdata = newdat, type = "lp") -
        predict(dfbeta.join, newdata = refdat, type = "lp"), lty = 4, col = "blue", lwd = 2)

# parameterwise shrunken
lines(age, predict(dfbeta.pw, newdata = newdat, type = "lp") -
        predict(dfbeta.pw, newdata =refdat, type = "lp"), lty = 2, col = "green", lwd = 2)

legend("topright", lty = c(1, 3, 4, 2), title = "SHRINKAGE",
       legend = c("No", "Global", "Joint", "Parameterwise"), inset = 0.01, bty = "n",
       col = c("black", "red", "blue", "green"), lwd = 2)