confint.segmented | R Documentation |
Computes confidence intervals for the breakpoints in a fitted ‘segmented’ model.
## S3 method for class 'segmented'
confint(object, parm, level=0.95, method=c("delta", "score", "gradient"),
rev.sgn=FALSE, var.diff=FALSE, is=FALSE, digits=max(4, getOption("digits") - 1),
.coef=NULL, .vcov=NULL, ...)
object |
a fitted |
parm |
the segmented variable of interest. If missing the first segmented variable in |
level |
the confidence level required, default to 0.95. |
method |
which confidence interval should be computed. One of |
rev.sgn |
vector of logicals. The length should be equal to the length of |
var.diff |
logical. If |
is |
logical. If |
digits |
controls the number of digits to print when returning the output. |
.coef |
The regression parameter estimates. If unspecified (i.e. |
.vcov |
The full covariance matrix of estimates. If unspecified (i.e. |
... |
additional parameters referring to Score-based confidence intervals, such as |
confint.segmented
computes confidence limits for the breakpoints. Currently there are three options, see argument method
.
method="delta"
uses the standard error coming from the Delta
method for the ratio of two random variables. This value is an approximation (slightly) better than the
one reported in the ‘psi’ component of the list returned by any segmented
method. The resulting
confidence intervals are based on the asymptotic Normal distribution of the breakpoint
estimator which is reliable just for clear-cut kink relationships. See Details in segmented
.
method="score"
or method="gradient"
compute the
confidence interval via profiling the Score or the Gradient statistics smoothed out by the induced smoothing paradigm, as discussed in the reference below.
A matrix including point estimate and confidence limits of the breakpoint(s) for the
segmented variable possibly specified in parm
.
Currently method="score"
or method="gradient"
only works for segmented linear model. For segmented generalized linear model, currently only method="delta"
is available.
Vito M.R. Muggeo
Muggeo, V.M.R. (2017) Interval estimation for the breakpoint in segmented regression: a smoothed score-based approach. Australian & New Zealand Journal of Statistics 59, 311–322.
segmented
and lines.segmented
to plot the estimated breakpoints with corresponding
confidence intervals.
set.seed(10)
x<-1:100
z<-runif(100)
y<-2+1.5*pmax(x-35,0)-1.5*pmax(x-70,0)+10*pmax(z-.5,0)+rnorm(100,0,2)
out.lm<-lm(y~x)
o<-segmented(out.lm,seg.Z=~x+z,psi=list(x=c(30,60),z=.4))
confint(o) #delta CI for the 1st variable
confint(o, "x", method="score") #also method="g"
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