ExProb {rms} | R Documentation |
Function Generator For Exceedance Probabilities
Description
For an orm
object generates a function for computing the
estimates of the function Prob(Y>=y) given one or more values of the
linear predictor using the reference (median) intercept. This
function can optionally be evaluated at only a set of user-specified
y
values, otherwise a right-step function is returned. There
is a plot method for plotting the step functions, and if more than one
linear predictor was evaluated multiple step functions are drawn.
ExProb
is especially useful for nomogram
.
Optionally a normal approximation for a confidence
interval for exceedance probabilities will be computed using the delta
method, if
conf.int > 0
is specified to the function generated from calling
ExProb
. In that case, a "lims"
attribute is included
in the result computed by the derived cumulative probability function.
Usage
ExProb(object, ...)
## S3 method for class 'orm'
ExProb(object, codes = FALSE, ...)
## S3 method for class 'ExProb'
plot(x, ..., data=NULL,
xlim=NULL, xlab=x$yname, ylab=expression(Prob(Y>=y)),
col=par('col'), col.vert='gray85', pch=20,
pch.data=21, lwd=par('lwd'), lwd.data=lwd,
lty.data=2, key=TRUE)
Arguments
object |
a fit object from |
codes |
if |
... |
ignored for |
data |
Specify |
x |
an object created by running the function created by |
xlim |
limits for x-axis; default is range of observed |
xlab |
x-axis label |
ylab |
y-axis label |
col |
color for horizontal lines and points |
col.vert |
color for vertical discontinuities |
pch |
plotting symbol for predicted curves |
lwd |
line width for predicted curves |
pch.data , lwd.data , lty.data |
plotting parameters for data |
key |
set to |
Value
ExProb
returns an R function. Running the function returns an
object of class "ExProb"
.
Author(s)
Frank Harrell and Shengxin Tu
See Also
Examples
set.seed(1)
x1 <- runif(200)
yvar <- x1 + runif(200)
f <- orm(yvar ~ x1)
d <- ExProb(f)
lp <- predict(f, newdata=data.frame(x1=c(.2,.8)))
w <- d(lp)
s1 <- abs(x1 - .2) < .1
s2 <- abs(x1 - .8) < .1
plot(w, data=data.frame(x1=c(rep(.2, sum(s1)), rep(.8, sum(s2))),
yvar=c(yvar[s1], yvar[s2])))
qu <- Quantile(f)
abline(h=c(.1,.5), col='gray80')
abline(v=qu(.5, lp), col='gray80')
abline(v=qu(.9, lp), col='green')