Function Generator For Exceedance Probabilities
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.
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)
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 |
ExProb
returns an R function. Running the function returns an
object of class "ExProb"
.
Frank Harrell and Shengxin Tu
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')
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