confint.segmented {segmented}R Documentation

Confidence intervals for breakpoints

Description

Computes confidence intervals for the breakpoints in a fitted `segmented' model.

Usage

## S3 method for class 'segmented':
confint(object, parm, level=0.95, rev.sgn=FALSE,
        digits=max(3, getOption("digits") - 3), ...)

Arguments

object a fitted segmented object.
parm the segmented variable of interest. If missing all the segmented variables are considered.
level the confidence level required (default to 0.95).
rev.sgn vector of logicals. The length should be equal to the length of parm; recycled otherwise. when TRUE it is assumed that the current parm is `minus' the actual segmented variable, therefore the sign is reversed before printing. This is useful when a null-constraint has been set on the last slope.
digits controls the number of digits to print when printing the output.
... additional parameters

Details

Currently confint.segmented computes confidence limits using standard errors coming from the Delta method for the ratio of two random variables of the estimated. This value is a better approximation of 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.

Value

A list of matrices. Each matrix includes point estimate and confidence limits of the breakpoint(s) for each segmented variable in the model.

Author(s)

Vito M.R. Muggeo

See Also

segmented

Examples

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)

[Package segmented version 0.2-4 Index]