plot.mfp {mfp} | R Documentation |
Plots for mfp objects
Description
This function draws two plots: (i) the linear predictor function and (ii) partial residuals together with a lowess smooth.
For Cox models also smoothed martingale based residuals of the null
model are plotted against the predictor.
Usage
## S3 method for class 'mfp':
plot(x, var=NULL, ref.zero=TRUE, ask=TRUE, ...)
Arguments
x |
object representing a fitted mfp model. |
var |
the variable for which plots are desired.
By default, plots are produced in turn for each variable of a model. |
ref.zero |
subtract a constant from X beta before plotting so that the
reference value of the 'x'-variable yields 'y=0'. |
ask |
logical; if 'TRUE', the user is asked before each plot, see 'par(ask=.)'. |
... |
further arguments. |
Examples
data(GBSG)
f <- mfp(Surv(rfst, cens) ~ fp(age, df = 4, select = 0.05)
+ fp(prm, df = 4, select = 0.05), family = cox, data = GBSG)
par(mfrow=c(2,2), mar=c(4,4,1,1), mgp=c(1.5,0.75,0))
plot(f, var="age")
[Package
mfp version 1.4.6
Index]